{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<p align=\"center\">\n",
    "    <img src=\"https://github.com/GeostatsGuy/GeostatsPy/blob/master/TCG_color_logo.png?raw=true\" width=\"220\" height=\"240\" />\n",
    "\n",
    "</p>\n",
    "\n",
    "## scikit learn for Prediction \n",
    "\n",
    "### scikit learn for Subsurface Modeling in Python \n",
    "\n",
    "#### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "\n",
    "##### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1) | [GeostatsPy](https://github.com/GeostatsGuy/GeostatsPy)\n",
    "\n",
    "### PGE 383 Exercise: scikit learn for Subsurface Modeling in Python \n",
    "\n",
    "Here's a simple workflow, demonstration of scikit learn for subsurface modeling workflows. This should help you get started with building subsurface models that data analytics and machine learning. Here's some basic details about scikit learn.  \n",
    "\n",
    "#### scikit learn\n",
    "\n",
    "Demonstration of scikit learn for machine learning.\n",
    "\n",
    "In this workflow we demonstrate the plug and play nature of scikit learn machine learning models.  \n",
    "\n",
    "For an unconventional dataset we demonstrate the following steps:\n",
    "    \n",
    "    1. instantiation\n",
    "    2. fitting\n",
    "    3. prediction\n",
    "    4. cross validation\n",
    "\n",
    "We will work with the following regression methods:\n",
    "\n",
    "* linear regression\n",
    "* multilinear regression\n",
    "* decision tree regression\n",
    "* support vector machine regression\n",
    "\n",
    "#### Getting Started\n",
    "\n",
    "Here's the steps to get setup in Python with the GeostatsPy package:\n",
    "\n",
    "1. Install Anaconda 3 on your machine (https://www.anaconda.com/download/). \n",
    "2. From Anaconda Navigator (within Anaconda3 group), go to the environment tab, click on base (root) green arrow and open a terminal. \n",
    "3. In the terminal type: pip install geostatspy. \n",
    "4. Open Jupyter and in the top block get started by copy and pasting the code block below from this Jupyter Notebook to start using the geostatspy functionality. \n",
    "\n",
    "There are examples below with these functions. You can go here to see a list of the available functions, https://git.io/fh4eX, other example workflows and source code. \n",
    "\n",
    "#### Import Required Packages\n",
    "\n",
    "Let's import the GeostatsPy package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os                                                 # to set current working directory \n",
    "import math                                               # basic calculations like square root\n",
    "from sklearn.model_selection import train_test_split      # train and test split\n",
    "from sklearn import svm                                   # support vector machine methods\n",
    "from sklearn import tree                                  # tree program from scikit learn (package for machine learning)\n",
    "from sklearn.metrics import mean_squared_error, r2_score  # specific measures to check our models\n",
    "import pandas as pd                                       # DataFrames and plotting\n",
    "import pandas.plotting as pd_plot\n",
    "import numpy as np                                        # arrays and matrix math\n",
    "import matplotlib.pyplot as plt                           # plotting\n",
    "from intake import cat                                    # data catalogue"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Declare functions\n",
    "\n",
    "Let's define a couple of functions to streamline plotting correlation matrices and visualization of a machine learning regression model responce over the 2 predictor features. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_corr(dataframe,size=10):                         # plots a graphical correlation matrix \n",
    "    corr = dataframe.corr()\n",
    "    fig, ax = plt.subplots(figsize=(size, size))\n",
    "    im = ax.matshow(corr,vmin = -1.0, vmax = 1.0)\n",
    "    plt.xticks(range(len(corr.columns)), corr.columns);\n",
    "    plt.yticks(range(len(corr.columns)), corr.columns);\n",
    "    plt.colorbar(im, orientation = 'vertical')\n",
    "    plt.title('Correlation Matrix')\n",
    "    \n",
    "def visualize_model(model,xfeature,yfeature,response,title,):# plots the data points and the decision tree prediction \n",
    "    n_classes = 10\n",
    "    cmap = plt.cm.RdYlBu\n",
    "    plot_step = 0.02\n",
    "    x_min, x_max = min(xfeature) - 1, max(xfeature) + 1\n",
    "    y_min, y_max = min(yfeature) - 1, max(yfeature) + 1\n",
    "    resp_min = round(min(response)); resp_max = round(max(response));\n",
    "    xx, yy = np.meshgrid(np.arange(x_min, x_max, plot_step),\n",
    "                     np.arange(y_min, y_max, plot_step))\n",
    "    z_min = round(min(response)); z_max = round(max(response))\n",
    "    Z = model.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "    cs = plt.contourf(xx, yy, Z, cmap=cmap,vmin=z_min, vmax=z_max)\n",
    "\n",
    "    im = plt.scatter(xfeature,yfeature,s=None, c=response, marker=None, cmap=cmap, norm=None, vmin=z_min, vmax=z_max, alpha=0.8, linewidths=0.3, verts=None, edgecolors=\"black\")\n",
    "    plt.title(title)\n",
    "    plt.xlabel(xfeature.name)\n",
    "    plt.ylabel(yfeature.name)\n",
    "    cbar = plt.colorbar(im, orientation = 'vertical')\n",
    "    cbar.set_label(response.name, rotation=270, labelpad=20)\n",
    "    return(plt)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Read the data table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data = cat.unconv_MV().read()                    # load the comma delimited data file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the first several rows of our data stored in a DataFrame so we can make sure we successfully loaded the data file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WellIndex</th>\n",
       "      <th>Por</th>\n",
       "      <th>LogPerm</th>\n",
       "      <th>AI</th>\n",
       "      <th>Brittle</th>\n",
       "      <th>TOC</th>\n",
       "      <th>VR</th>\n",
       "      <th>Production</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>15.91</td>\n",
       "      <td>1.67</td>\n",
       "      <td>3.06</td>\n",
       "      <td>14.05</td>\n",
       "      <td>1.36</td>\n",
       "      <td>1.85</td>\n",
       "      <td>177.381958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>15.34</td>\n",
       "      <td>1.65</td>\n",
       "      <td>2.60</td>\n",
       "      <td>31.88</td>\n",
       "      <td>1.37</td>\n",
       "      <td>1.79</td>\n",
       "      <td>1479.767778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>20.45</td>\n",
       "      <td>2.02</td>\n",
       "      <td>3.13</td>\n",
       "      <td>63.67</td>\n",
       "      <td>1.79</td>\n",
       "      <td>2.53</td>\n",
       "      <td>4421.221583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>11.95</td>\n",
       "      <td>1.14</td>\n",
       "      <td>3.90</td>\n",
       "      <td>58.81</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2.03</td>\n",
       "      <td>1488.317629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>19.53</td>\n",
       "      <td>1.83</td>\n",
       "      <td>2.57</td>\n",
       "      <td>43.75</td>\n",
       "      <td>1.40</td>\n",
       "      <td>2.11</td>\n",
       "      <td>5261.094919</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   WellIndex    Por  LogPerm    AI  Brittle   TOC    VR   Production\n",
       "0          1  15.91     1.67  3.06    14.05  1.36  1.85   177.381958\n",
       "1          2  15.34     1.65  2.60    31.88  1.37  1.79  1479.767778\n",
       "2          3  20.45     2.02  3.13    63.67  1.79  2.53  4421.221583\n",
       "3          4  11.95     1.14  3.90    58.81  0.40  2.03  1488.317629\n",
       "4          5  19.53     1.83  2.57    43.75  1.40  2.11  5261.094919"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data.head()                                            # preview the first 5 rows of the dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's remove the well index and check the summary summary statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Por</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>14.950460</td>\n",
       "      <td>3.029634</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>12.85750</td>\n",
       "      <td>14.98500</td>\n",
       "      <td>17.080000</td>\n",
       "      <td>24.65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LogPerm</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.398880</td>\n",
       "      <td>0.405966</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>1.13000</td>\n",
       "      <td>1.39000</td>\n",
       "      <td>1.680000</td>\n",
       "      <td>2.58000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AI</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>2.982610</td>\n",
       "      <td>0.577629</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>2.57750</td>\n",
       "      <td>3.01000</td>\n",
       "      <td>3.360000</td>\n",
       "      <td>4.70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brittle</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>49.719480</td>\n",
       "      <td>15.077006</td>\n",
       "      <td>-10.500000</td>\n",
       "      <td>39.72250</td>\n",
       "      <td>49.68000</td>\n",
       "      <td>59.170000</td>\n",
       "      <td>93.47000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOC</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.003810</td>\n",
       "      <td>0.504978</td>\n",
       "      <td>-0.260000</td>\n",
       "      <td>0.64000</td>\n",
       "      <td>0.99500</td>\n",
       "      <td>1.360000</td>\n",
       "      <td>2.71000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VR</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.991170</td>\n",
       "      <td>0.308194</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>1.81000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>2.172500</td>\n",
       "      <td>2.90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Production</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>2247.295809</td>\n",
       "      <td>1464.256312</td>\n",
       "      <td>2.713535</td>\n",
       "      <td>1191.36956</td>\n",
       "      <td>1976.48782</td>\n",
       "      <td>3023.594214</td>\n",
       "      <td>12568.64413</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             count         mean          std        min         25%  \\\n",
       "Por         1000.0    14.950460     3.029634   5.400000    12.85750   \n",
       "LogPerm     1000.0     1.398880     0.405966   0.120000     1.13000   \n",
       "AI          1000.0     2.982610     0.577629   0.960000     2.57750   \n",
       "Brittle     1000.0    49.719480    15.077006 -10.500000    39.72250   \n",
       "TOC         1000.0     1.003810     0.504978  -0.260000     0.64000   \n",
       "VR          1000.0     1.991170     0.308194   0.900000     1.81000   \n",
       "Production  1000.0  2247.295809  1464.256312   2.713535  1191.36956   \n",
       "\n",
       "                   50%          75%          max  \n",
       "Por           14.98500    17.080000     24.65000  \n",
       "LogPerm        1.39000     1.680000      2.58000  \n",
       "AI             3.01000     3.360000      4.70000  \n",
       "Brittle       49.68000    59.170000     93.47000  \n",
       "TOC            0.99500     1.360000      2.71000  \n",
       "VR             2.00000     2.172500      2.90000  \n",
       "Production  1976.48782  3023.594214  12568.64413  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_data = my_data.iloc[:,1:8]                             # copy all rows and columns 1 through 8, note 0 column is removed\n",
    "my_data.describe().transpose()                            # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is good that we checked the summary statistics, because we have some negative values for brittleness and total organic carbon. The is physically imposible.  The values must be in error. We know the lowest possible values are 0.0, so we will truncate on 0.0.  We use the *get_numerical_data()* DataFrame member function to get a shallow copy of the data from the DataFrame.  Since it is a shallow copy, any changes we make to the copy are made to the data in the original DataFrame.  This allows us to apply this simple conditional statement to all the data values in the DataFrame all at once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Por</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>14.950460</td>\n",
       "      <td>3.029634</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>12.85750</td>\n",
       "      <td>14.98500</td>\n",
       "      <td>17.080000</td>\n",
       "      <td>24.65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LogPerm</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.398880</td>\n",
       "      <td>0.405966</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>1.13000</td>\n",
       "      <td>1.39000</td>\n",
       "      <td>1.680000</td>\n",
       "      <td>2.58000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AI</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>2.982610</td>\n",
       "      <td>0.577629</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>2.57750</td>\n",
       "      <td>3.01000</td>\n",
       "      <td>3.360000</td>\n",
       "      <td>4.70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brittle</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>49.731480</td>\n",
       "      <td>15.033593</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>39.72250</td>\n",
       "      <td>49.68000</td>\n",
       "      <td>59.170000</td>\n",
       "      <td>93.47000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOC</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.006170</td>\n",
       "      <td>0.499838</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.64000</td>\n",
       "      <td>0.99500</td>\n",
       "      <td>1.360000</td>\n",
       "      <td>2.71000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VR</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.991170</td>\n",
       "      <td>0.308194</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>1.81000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>2.172500</td>\n",
       "      <td>2.90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Production</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>2247.295809</td>\n",
       "      <td>1464.256312</td>\n",
       "      <td>2.713535</td>\n",
       "      <td>1191.36956</td>\n",
       "      <td>1976.48782</td>\n",
       "      <td>3023.594214</td>\n",
       "      <td>12568.64413</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             count         mean          std       min         25%  \\\n",
       "Por         1000.0    14.950460     3.029634  5.400000    12.85750   \n",
       "LogPerm     1000.0     1.398880     0.405966  0.120000     1.13000   \n",
       "AI          1000.0     2.982610     0.577629  0.960000     2.57750   \n",
       "Brittle     1000.0    49.731480    15.033593  0.000000    39.72250   \n",
       "TOC         1000.0     1.006170     0.499838  0.000000     0.64000   \n",
       "VR          1000.0     1.991170     0.308194  0.900000     1.81000   \n",
       "Production  1000.0  2247.295809  1464.256312  2.713535  1191.36956   \n",
       "\n",
       "                   50%          75%          max  \n",
       "Por           14.98500    17.080000     24.65000  \n",
       "LogPerm        1.39000     1.680000      2.58000  \n",
       "AI             3.01000     3.360000      4.70000  \n",
       "Brittle       49.68000    59.170000     93.47000  \n",
       "TOC            0.99500     1.360000      2.71000  \n",
       "VR             2.00000     2.172500      2.90000  \n",
       "Production  1976.48782  3023.594214  12568.64413  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num = my_data._get_numeric_data()                         # get the numerical values\n",
    "num[num < 0] = 0                                          # truncate negative values to 0.0\n",
    "my_data.describe().transpose()                            # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This dataset has variables from 1,000 unconventional wells including well average porosity, log transform of permeability (to linearize the relationships with other variables), accoustic impedance (kg/m2s*10^6), brittness ratio (%), total organic carbon (%), vitrinite reflectance (%), and initial production 90 day average (MCFPD).  Note, the dataset is synthetic.\n",
    "\n",
    "#### Calculate the correlation matrix \n",
    "\n",
    "For multivariate analysis it is a good idea to check the correlation matrix.  We can calculate it and view it in the console with these commands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1.    0.81 -0.51 -0.25  0.71  0.08  0.69]\n",
      " [ 0.81  1.   -0.32 -0.15  0.51  0.05  0.57]\n",
      " [-0.51 -0.32  1.    0.17 -0.55  0.49 -0.33]\n",
      " [-0.25 -0.15  0.17  1.   -0.24  0.3  -0.07]\n",
      " [ 0.71  0.51 -0.55 -0.24  1.    0.31  0.5 ]\n",
      " [ 0.08  0.05  0.49  0.3   0.31  1.    0.14]\n",
      " [ 0.69  0.57 -0.33 -0.07  0.5   0.14  1.  ]]\n"
     ]
    }
   ],
   "source": [
    "corr_matrix = np.corrcoef(my_data, rowvar = False)\n",
    "print(np.around(corr_matrix,2))                           # print the correlation matrix to 2 decimals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note the 1.0 diagonal resulting from the correlation of each variable with themselves.  \n",
    "\n",
    "Let's use our function declared above to make a graphical correlation matrix visualization.  This may inprove our ability to spot features.  It relies on the built in correlation matrix method with Numpy DataFrames and MatPlotLib for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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U/gvgy8Ducw3+Z/RztiKjC0MuZp5XNQ9Jk2Q8B3hekkuB7wC30Pz/bwb5HwT834xul/EtRkMbftFTlxfaR4A9uetU/myfYvQd86SW+YPRFJJHMvqZ/SZwblV9uml/A3AG8EVGwzJm/BujguosRqc8b2q29TlGp+dXNn9//qpZ/ljg3TOD/9e27w10qOpI7ko6pQ2j+e3v5qqqJAcBB1fVAX33S5LUvd0fs2l98DPdhL977XLlOVW1opOdLRDPOasLezEarB3gZ8BLeu6PJEmDZGGmDa6qvsrotIUkaZErwmpHUrXyk5EkSRoIEzNJktSpab1isgsmZgOT5LC++9CXxXzs4PF7/Iv3+BfzsYPHr7uzMBuexfwXdDEfO3j8Hv/itZiPHRbZ8Xvn/8kszCRJkgbCMWazLH3gklq20yZrX3AD2XmH+7Biz/v2dnO5G3q8rd22D7kPj3xMf8cO8MMrl/a27802fwBbbr1jr8e/etP+fsPcZKut2XzbnXo7/u0edH1fuwZgm4dsykP32LK347/qhgf0tWuWPPABbLZLvz/722018b7XG9QDH7IZu+yxVW/Hf+0Pb+HG62+fznhpI2RhNsuynTbhrFN26rsbvTn9lr570K+/ffWiOqNwDz9ftni/Ev7y5R/ruwu9ev1pv993F3p1+JM/23cXevOW557T8R7D6vKEXRs/GUmSpIFYvL8eS5KkzhWwxlyolZ+MJEnSQJiYSZKkTk3rrSy6YGImSZI0ECZmkiSpM1VelTmJn4wkSdJAmJhJkqROrXGMWSsTM0mSpIEwMZMkSZ0ZPcTcXKiNn4wkSdJAmJhJkqQOeVXmJH4ykiRJA2FiJkmSOuOzMifzk5EkSYtWkmckuSTJZUmOmGP+25Kc17y+k+RnY/NWj807aSH6Y2ImSZIWpSRLgHcC+wOrgLOTnFRVF88sU1V/Mbb8/wYeO7aJm6tq+UL2ycJMkiR1anUN5gazewOXVdUVAElOAA4ALm5Z/mDg9RuyQ57KlCRJG6ulSVaOvQ6bNX8H4Mqx6VVN2z0k2QV4KPClseb7Nts9M8mBC9FhEzNJktSZIl3eYPaaqloxYf5c0V21LHsQcGJVrR5r27mqrkryMOBLSS6oqsvvbWfBxEySJC1eq4CdxqZ3BK5qWfYg4CPjDVV1VfPnFcBp3H382b1iYiZJkjq1Zjg3mD0b2DXJQ4EfMiq+Xjh7oSSPBLYGzhhr2xr4ZVXdmmQp8ETgrevbIQszSZK0KFXVHUleCZwCLAHeX1UXJTkKWFlVM7fAOBg4oarGT3PuBrwnyRpGZyCPHr+a896yMJMkSZ0Z2kPMq+pk4ORZba+bNf2GOdb7GvDohe7PcD4ZSZKkRc7ETJIkdabIkO5jNjgmZpIkSQNhYiZJkjrlQ8zbTW1hlmQ1cAGjY/gWcEhV/bLfXkmSJN1701yy3lxVy6tqD+A24OXzWSkj03zckiRNrSpYXb/SyWsaTWev7+mrwCMAkrw6yYXN61VN27Ik30ryLuBc7n6XX0mSpEGY2lOZM5LcB3gm8LkkewEvBvZh9Pyrryf5CnA98EjgxVX1Z3Ns4zDgMICdd5j6j0SSpAELa+Z8RKVguhOzzZOcB6wEfgC8D/gt4JNVdVNV3Qj8B/CkZvnvV9WZc22oqo6pqhVVteJB2yzpou+SJEn3MM3x0M1VtXy8IcmkEvymDdwfSZKk9TLNhdlcTgeOTXI0o1OZzwH+uN8uSZKkGQVTOzC/CxtVYVZV5yY5FjiraXpvVX0jybLeOiVJkjRPU1uYVdWWLe3/BPzTrLbvAXt00C1JkrQWQ3qI+dD4yUiSJA3E1CZmkiRp+hRhjQ8xb2ViJkmSNBAmZpIkqVOOMWvnJyNJkjQQJmaSJKkzBazxPmat/GQkSZIGwsRMkiR1KKz2IeatTMwkSZIGwsRMkiR1xjFmk/nJSJIkDYSJmSRJ6pRjzNqZmEmSJA2EiZkkSepMVRxjNoGfjCRJ0kBYmEmSJA2EpzIlSVKnVnsqs5WfjCRJ0kCYmEmSpM4UsMbbZbQyMZMkSRoIEzNJktShOMZsAj8ZSZKkgTAxkyRJnRk9xNwxZm1MzCRJkgbCxEySJHVqtblQKwuzWW4oOP2WvnvRnyfft+8e9OumbZf03YVe3b5l3z3oz5d/tlvfXehV7ljcp5YuvXnbvrvQm1vWbNJ3FzTGwkySJHWmiGPMJjBLlCRJGggTM0mS1Kk15kKt/GQkSZIGwsRMkiR1pgpWO8aslYmZJEnSQFiYSZIkDYSnMiVJUqe8XUY7EzNJkqSBMDGTJEmdGd1g1lyojZ+MJEnSQJiYSZKkTq3GMWZtTMwkSZIGwsRMkiR1pvCqzElMzCRJkgbCxEySJHXIqzIn8ZORJEkaCBMzSZLUqTVeldnKxEySJGkgTMwkSVJnqmC1V2W2MjGTJEmLVpJnJLkkyWVJjphj/qFJfprkvOb1srF5hyS5tHkdshD9MTGTJEmdGspVmUmWAO8E9gdWAWcnOamqLp616Eer6pWz1n0g8HpgBaPbs53TrHv9+vRpGJ+MJElS9/YGLquqK6rqNuAE4IB5rvt04AtVdV1TjH0BeMb6dsjCTJIkbayWJlk59jps1vwdgCvHplc1bbP9QZLzk5yYZKd1XHedeCpTkiR1pkiXj2S6pqpWTJg/V0dq1vR/Ah+pqluTvBw4Dth3nuuuMxMzSZK0WK0Cdhqb3hG4anyBqrq2qm5tJv8N2Gu+694bFmaSJKlTa0gnr3k4G9g1yUOTbAocBJw0vkCS7ccmnw18q3l/CvC0JFsn2Rp4WtO2XjyVKUmSFqWquiPJKxkVVEuA91fVRUmOAlZW1UnAnyd5NnAHcB1waLPudUn+nlFxB3BUVV23vn1asMIsyY1VteV6bmMZo0r0EmBT4HTgz6pqzXp3UJIk9a6gyzFma1VVJwMnz2p73dj7I4EjW9Z9P/D+hezPEE9lXl5Vy4HHALsDB85npYwM8XgkSZLmZYMWMkl2SXJqc4npqUl2btofnuTMJGcnOSrJjbPXrao7gK8Bj2jWeU2z/PlJ3ti0LUvyrSTvAs4FdkpyY5K3JDknyReT7J3ktCRXNFGkJEnq0Zr6lU5e02hD9/odwPFV9RjgQ8C/NO1vB95eVY+j5QqGJFsATwUuSPI0YFdGN4JbDuyV5MnNoo9s9vHYqvo+cD/gtKraC7gBeBOjO/o+BziqZV+Hzdzj5OfXrl7vg5YkSbo3NnRh9gTgw837fwd+a6z94837D89a5+FJzgP+B/hsVf0XoysdngZ8g1Ey9ihGhRrA96vqzLH1bwM+17y/APhKVd3evF82Vyer6piqWlFVK351myXrfJCSJGmeanQfsy5e06jrqzLnc+O1mTFm4wL8Q1W9526No4sFbpq17O1VNbOfNcCtAFW1JolXoUqSpMHa0InZ1xjdEwTgD4H/bt6fCfxB8/6g2SvN4RTgJUm2BEiyQ5IHL2RHJUnShlcM6j5mg7OQCdIWSVaNTf8T8OfA+5O8Bvgp8OJm3quADyb5S+CzwM8nbbiqPp9kN+CMJAA3An8EOCBMkiRtNBasMKtqvfxh3znafgg8vqoqyUHAymYb3wP2aNn+2xldNDDbHrOW23Ls/Rva5kmSpH5M6/ivLvQ15mov4B0ZxV8/A17SUz8kSZIGo5fCrKq+CuzZx74lSVJ/hnbn/6GZzruvSZIkbYQszCRJkgbC+3pJkqROeSqznYmZJEnSQJiYSZKkzhTT+7ikLpiYSZIkDYSJmSRJ6tS0Pi6pCyZmkiRJA2FiJkmSulNelTmJiZkkSdJAmJhJkqTO+EimyUzMJEmSBsLETJIkdcrErJ2JmSRJ0kCYmEmSpM545//JTMwkSZIGwsRMkiR1qkzMWpmYSZIkDYSFmSRJ0kB4KlOSJHXKh5i3MzGTJEkaCBMzSZLUmfIh5hOZmEmSJA2EiZkkSeqUt8toZ2E2yw+vXMrfvvqwvrvRm5u2XdJ3F3p1zuv/te8u9Orhp7647y705rtvfFTfXejVb/7dJX13oVenHbNP313ozQ3XfK3vLmiMhZkkSeqQj2SaxDFmkiRJA2FiJkmSOuUYs3YmZpIkSQNhYiZJkjpTeB+zSUzMJEmSBsLETJIkdadGd//X3EzMJEmSBsLETJIkdWoNjjFrY2ImSZI0EBZmkiRJA+GpTEmS1JnCG8xOYmImSZI0ECZmkiSpQz7EfBITM0mSpIEwMZMkSZ3yBrPtTMwkSZIGwsRMkiR1yqsy25mYSZIkDYSJmSRJ6kyVidkkJmaSJEkDYWImSZI65X3M2pmYSZIkDYSJmSRJ6pT3MWtnYiZJkhatJM9IckmSy5IcMcf8Vye5OMn5SU5NssvYvNVJzmteJy1Ef0zMJElSp4ZyVWaSJcA7gf2BVcDZSU6qqovHFvsGsKKqfpnkT4G3Ai9o5t1cVcsXsk8mZpIkabHaG7isqq6oqtuAE4ADxheoqi9X1S+byTOBHTdkhyzMJEnSxmppkpVjr8Nmzd8BuHJselXT1ualwH+NTd+32e6ZSQ5ciA5vlKcykzwH+A9gt6r6dpJlwGeqao9eOyZJ0iJXpMtTmddU1YoJ8+fqyJyXJiT5I2AF8NtjzTtX1VVJHgZ8KckFVXX5ve/uxpuYHQz8N3BQ3x2RJEmDtQrYaWx6R+Cq2Qsl2Q94LfDsqrp1pr2qrmr+vAI4DXjs+nZooyvMkmwJPJFR3GhhJknSwFRHr3k4G9g1yUOTbMqobrjb1ZVJHgu8h1FR9pOx9q2TbNa8X8qo9hi/aOBe2RhPZR4IfK6qvpPkuiS/AVw3aYXmnPNhAJtt/oAOuihJkvpWVXckeSVwCrAEeH9VXZTkKGBlVZ0E/B9gS+DjSQB+UFXPBnYD3pNkDaOg6+hZV3PeKxtjYXYw8M/N+xOa6XdOWqGqjgGOAdhy6x297Z0kSRvKwB5iXlUnAyfPanvd2Pv9Wtb7GvDohe7PRlWYJdkG2BfYI0kxqn4LeFevHZMkSZqHjW2M2XOB46tql6paVlU7Ad9lA99zRJIkrYMBDTIbmo2tMDsY+OSstk8Af9NDXyRJktbJRnUqs6qeMkfbvwD/0n1vJEnSXIY0xmxoNrbETJIkaWptVImZJEkavprS8V9dMDGTJEkaCBMzSZLUmcIxZpOYmEmSJA2EiZkkSepOASZmrUzMJEmSBsLCTJIkaSA8lSlJkjrl7TLamZhJkiQNhImZJEnqlolZKxMzSZKkgTAxkyRJHYo3mJ3AxEySJGkgTMwkSVK3HGPWysRMkiRpIEzMJElSd8qHmE9iYiZJkjQQJmaSJKlbjjFrZWImSZI0ECZmkiSpY44xa2NiJkmSNBAmZpIkqVuOMWtlYiZJkjQQFmaSJEkD4anMWVZvGn6+bPF+LLdv2XcP+vXwU1/cdxd6dflTP9B3F3qz57l/1ncXevXzn27Xdxd6ddMuffegP2s27WGnnspsZWImSZI0EIs3GpIkSd0rwEcytTIxkyRJGggTM0mS1KlyjFkrEzNJkqSBMDGTJEndMjFrZWImSZI0ECZmkiSpW16V2crETJIkaSBMzCRJUqfiGLNWJmaSJEkDYWImSZK6U3hV5gQmZpIkSQNhYiZJkjoUr8qcwMRMkiRpICzMJEmSBsJTmZIkqVsO/m9lYiZJkjQQJmaSJKlbJmatTMwkSZIGwsRMkiR1y8SslYmZJEnSQJiYSZKk7hTeYHYCEzNJkqSBMDGTJEmdimPMWpmYSZIkDYSJmSRJ6paJWSsTM0mSpIGwMJMkSRqIXguzJKuTnJfkm0nOTfKbE5b9WvPnsiQvHGtfnuRZY9OHJnnHhu25JEnaGCR5RpJLklyW5Ig55m+W5KPN/K8nWTY278im/ZIkT1+I/vSdmN1cVcurak/gSOAfZi+QZAlAVc0UbcuAF44tshx4FpIkaSqkunmttR+jGuOdwDOB3YGDk+w+a7GXAtdX1SOAtwFvadbdHTgI+HXgGcC7ZmqW9dF3YTbu/sD1AEmekuTLST4MXNC03dgsdzTwpCZpOxw4CnhBM/2C8Q0meVCSTyQ5u3k9sbvDkSRJA7c3cFlVXVFVtwEnAAfMWuYA4Ljm/YnAU5OkaT+hqm6tqu8ClzXbWy99X+FzWkoAABT2SURBVJW5eZLzgPsC2wP7js3bG9ijOdhxRwB/VVW/C5Dkx8CKqnplM33o2LJvB95WVf+dZGfgFGC32Z1IchhwGMAmW229EMclSZLadHfn/6VJVo5NH1NVx4xN7wBcOTa9Cthn1jbuXKaq7kjyc2Cbpv3MWevusL4d7rswu7mqlgMkeQJwfJI9mnlnzVGUrav9gN1HhS0A90+yVVXdML5Q8z/pGIDNt93Ji3glSdo4XFNVKybMn6tCnF0HtC0zn3XXWd+F2Z2q6owkS4EHNU03LcBmfwV4QlXdvADbkiRJG5dVwE5j0zsCV7UssyrJfYBfBa6b57rrbDBjzJI8ClgCXLuWRW8AtpowPe7zwCvH9rF8ffooSZLWU3X4WruzgV2TPDTJpowG8580a5mTgEOa988FvlRV1bQf1Fy1+VBgV+Cs+X8Qc+s7MZsZYwajSPCQqlo9dupxLucDdyT5JnAsowF5RzTbmX1V558D70xyPqNjPR14+QL2X5IkTalmzNgrGY1BXwK8v6ouSnIUsLKqTgLeB/x7kssYJWUHNetelORjwMXAHcArqmr1+vap18Ksqua8rLSqTgNOm9W2ZfPn7cBTZ63yuFnTxzbLXgO8AEmSNBwDGs1dVScDJ89qe93Y+1uA57Ws+2bgzQvZn8GcypQkSVrs+j6VKUmSFpn53Px1sTIxkyRJGggTM0mS1C0Ts1YmZpIkSQNhYiZJkrplYtbKxEySJGkgTMwkSVJnUl6VOYmJmSRJ0kCYmEmSpG7VxEcvLmomZpIkSQNhYiZJkrrlGLNWJmaSJEkDYWEmSZI0EJ7KlCRJnfJ2Ge1MzCRJkgbCxEySJHXLxKyViZkkSdJAmJhJkqTu+EimiUzMJEmSBsLETJIkdcvErJWJmSRJ0kCYmEmSpG6ZmLUyMZMkSRoIEzNJktQpr8psZ2E2y3YPup6/fPnH+u5Gb778s9367kKvvvvGR/XdhV7tee6f9d2F3nzzNe/quwu92uuc5/fdhV49cd8L++5Cbz573M19d0FjPJUpSZI0EBZmkiRJA+GpTEmS1C3HmLUyMZMkSRoICzNJkqSB8FSmJEnqjg8xn8jETJIkaSBMzCRJUrdMzFqZmEmSJA2EiZkkSeqWiVkrEzNJkqSBMDGTJEmdCV6VOYmJmSRJ0kCYmEmSpG6ZmLUyMZMkSRoIEzNJktQd7/w/kYmZJEnSQJiYSZKkbpmYtTIxkyRJGggTM0mS1C0Ts1YmZpIkSQNhYSZJkjQQnsqUJEmd8nYZ7UzMJEmSBsLETJIkdcvErJWJmSRJ0kCYmEmSpO4UJmYTmJhJkiQNhImZJEnqlFdltht8YpZkmyTnNa8fJfnh2PTOST6d5NIklyd5e5JNx9bdO8npSS5J8u0k702yRZ/HI0mS1GbwhVlVXVtVy6tqOfBu4G3N+8cCJwKfqqpdgV8DtgTeDJBkW+DjwOFV9UhgN+BzwFY9HIYkSZpRHb2m0OALswn2BW6pqg8AVNVq4C+AlzSp2CuA46rqjGZ+VdWJVfXj3nosSZI0wTQXZr8OnDPeUFW/AH4APALYY/b8NkkOS7Iyycobrr99wTsqSZLukurmNY2muTALcweVbe2tquqYqlpRVSu22nqTBemcJEmaXkkemOQLzTj2LyTZeo5llic5I8lFSc5P8oKxeccm+e7YuPjl89nvNBdmFwErxhuS3B/YCbi8mb9XD/2SJEmTTMcYsyOAU5tx7Kc207P9EnhRVf068Azgn5M8YGz+a2bGyVfVefPZ6TQXZqcCWyR5EUCSJcA/AsdW1S+BdwCHJNlnZoUkf5Rku156K0mSpskBwHHN++OAA2cvUFXfqapLm/dXAT8BHrQ+O53awqyqCngO8LwklwLfAW4B/qaZ/2PgIOD/NrfL+BbwJOAXPXVZkiR1lZaNErOlM2PIm9dh69DTbavqaoDmzwdPWjjJ3sCmjM7azXhzc4rzbUk2m89Op+oGs1X1hlnTVwK/N2H5MxgVY5IkafG5pqpWtM1M8kVgrjNpr12XnSTZHvh34JCqWtM0Hwn8iFGxdgxwOHDU2rY1VYWZJEnSQqmq/drmJflxku2r6uqm8PpJy3L3Bz4L/G1VnTm27aubt7cm+QDwV/Pp09SeypQkSdMnHb7W00nAIc37Q4BP3+NYRk8b+iRwfFV9fNa87Zs/w2h82oXz2amFmSRJ0j0dDezfjGPfv5kmyYok722WeT7wZODQOW6L8aEkFwAXAEuBN81np57KlCRJ3ZqCm79W1bXAU+doXwm8rHn/QeCDLevve2/2a2ImSZI0ECZmkiSpU9P6uKQumJhJkiQNhImZJEnqlolZKxMzSZKkgTAxkyRJ3TIxa2ViJkmSNBAmZpIkqTvlVZmTmJhJkiQNhImZJEnqlolZKxMzSZKkgTAxkyRJnXKMWTsTM0mSpIGwMJMkSRoIT2VKkqRueSqzlYmZJEnSQJiYSZKkTjn4v52JmSRJ0kCYmEmSpO4UjjGbwMRMkiRpIEzMJElSt0zMWlmYzXLVDQ/g9af9ft/d6E3uSN9d6NVv/t0lfXehVz//6XZ9d6E3e53z/L670Ktz9vpY313o1cM+/9K+u9CbG265b99d0BgLM0mS1JngVZmTOMZMkiRpIEzMJElSt0zMWpmYSZIkDYSJmSRJ6lTKyKyNiZkkSdJAmJhJkqTueOf/iUzMJEmSBsLCTJIkaSA8lSlJkjrlDWbbmZhJkiQNhImZJEnqlolZKxMzSZKkgTAxkyRJnXKMWTsTM0mSpIEwMZMkSd0yMWtlYiZJkjQQJmaSJKk75RizSUzMJEmSBsLETJIkdcvErJWJmSRJ0kCYmEmSpM4Ex5hNYmImSZI0ECZmkiSpW2Vk1sbETJIkaSAszCRJkgbCU5mSJKlTDv5vZ2ImSZI0ECZmkiSpO4U3mJ1gqhOzJKclefqstlclOTnJzUnOS3JxkuOTbNJXPyVJkuZjqgsz4CPAQbPaDgL+Abi8qpYDjwZ2BJ7fcd8kSdIcsqab1zSa9sLsROB3k2wGkGQZ8BBg1cwCVbUaOAvYoYf+SZIkzdtUF2ZVdS2jousZTdNBwEcZO3ud5L7APsDn2raT5LAkK5OsXH3jTRuwx5Ik6c5xZhv6NYWmujBrjJ/OPKiZBnh4kvOAa4EfVNX5bRuoqmOqakVVrViy5f02bG8lSZJabAyF2aeApyb5DWDzqjq3aZ8ZY/YI4PFJnt1bDyVJ0p1S3bym0dQXZlV1I3Aa8H7uSsvG518NHAEc2W3PJEmS1s3UF2aNjwB7Aie0zP8UsEWSJ3XXJUmSdA/F6CHmXbym0EZxg9mq+iSQsenvAXuMTRejwk2SJGmtkjyQ0QWFy4DvAc+vquvnWG41cEEz+YOqenbT/lBGgdEDgXOBP66q29a2340lMZMkSVNiSsaYHQGcWlW7Aqc203O5uaqWN6/x8exvAd7WrH898NL57NTCTJIk6Z4OAI5r3h8HHDjfFZME2JfR/VbXaX0LM0mS1K3u7mO2dOY+pc3rsHXo5bbNBYQzFxI+uGW5+zbbPjPJTPG1DfCzqrqjmV7FPG90v1GMMZMkSZrDNVW1om1mki8C280x67XrsI+dq+qqJA8DvpTkAuAXcyw3r5OrFmaSJGlRqqr92uYl+XGS7avq6iTbAz9p2cZVzZ9XJDkNeCzwCeABSe7TpGY7AlfNp0+eypQkSZ0JUzP4/yTgkOb9IcCn73EsydZjz+teCjwRuLi5G8SXgedOWn8uFmaSJEn3dDSwf5JLgf2baZKsSPLeZpndgJVJvsmoEDu6qi5u5h0OvDrJZYzGnL1vPjv1VKYkSerOlNz8taquBZ46R/tK4GXN+68Bj25Z/wpg73Xdr4mZJEnSQJiYSZKkTk3rA8a7YGImSZI0ECZmkiSpWyZmrUzMJEmSBsLETJIkdcoxZu1MzCRJkgbCxEySJHWngDVGZm1MzCRJkgbCxEySJHXLwKyViZkkSdJAmJhJkqROeVVmOxMzSZKkgbAwkyRJGghPZUqSpG6V5zLbmJhJkiQNhImZJEnqlIP/21mYzbLdVj/n8Cd/tu9u9ObSm7ftuwu9Ou2YffruQq9u2qXvHvTnifte2HcXevWwz7+07y706oqnva/vLvRm73+8pu8uaIyFmSRJ6k7hDWYncIyZJEnSQJiYSZKkzgSIV2W2MjGTJEkaCBMzSZLUrTV9d2C4TMwkSZIGwsRMkiR1yjFm7UzMJEmSBsLETJIkdcf7mE1kYiZJkjQQJmaSJKlDBY4xa2ViJkmSNBAmZpIkqVMxMGtlYiZJkjQQFmaSJEkD4alMSZLULQf/tzIxkyRJGggTM0mS1J2C+BDzViZmkiRJA2FiJkmSuuUYs1YmZpIkSQNhYiZJkrplYNbKxEySJGkgTMwkSVKn4hizViZmkiRJA2FiJkmSumVi1srETJIkaSBMzCRJUncK8M7/rdaamCVZneS8JBcm+XiSLe7tzpIcmuQd67HuQ8am35tk93vbF0mSpKGZz6nMm6tqeVXtAdwGvHx8Zka6OCV6KHBnYVZVL6uqizvYryRJWiChSHXzmkbrWlB9FXhEkmVJvpXkXcC5wE5JDk5yQZOsvWVmhSQvTvKdJF8BnjjWfmyS545N3zj2/q+bbX0zydHNciuADzXp3eZJTkuyolm+bd83Jnlzs50zk2y7jscrSZLUmXkXZknuAzwTuKBpeiRwfFU9FrgdeAuwL7AceFySA5NsD7yRUUG2P7DWU49JngkcCOxTVXsCb62qE4GVwB826d3NY8s/ZK59N7PvB5zZbOd04E9a9nlYkpVJVt54/e3z/UgkSZIW1HwKs82TnMeoMPoB8L6m/ftVdWbz/nHAaVX106q6A/gQ8GRgn7H224CPzmN/+wEfqKpfAlTVdWtZvm3fMDr1+pnm/TnAsrk2UFXHVNWKqlqx5dabzKOLkiTpXqvq5jWF5nNV5s1VtXy8IQnATeNNE9Zv+2TuoCkMM9rgpmPbWpdPc9K+b6+68//MarwKVZIkDdhCDdr/OvDbSZYmWQIcDHylaX9Kkm2SbAI8b2yd7wF7Ne8PAGaiqs8DL5m5+jPJA5v2G4Ct1mHfkiRpiEzMWi1IglRVVyc5EvgyowTr5Kr6NECSNwBnAFczulBgSbPavwGfTnIWcCpNAldVn0uyHFiZ5DbgZOBvgGOBdye5GXjCfPYtSZI0TdZamFXVlnO0fQ/YY1bbh4EPz7HsB4APzNH+Y+DxY01Hjs07Gjh61vKfAD4x1vSUeex7y7H3JwInzl5GkiR1yBvMTuQjmSRJkgbCwfCSJKlT03rz1y6YmEmSJA2EiZkkSeqWiVkrEzNJkqRZkjwwyReSXNr8ufUcy/xO86jImdctM08fah49+d2xecvvuZd7sjCTJEkd6ugeZuufyh0BnFpVuzK6rdcR9ziSqi83j4pczujRkL9kdD/WGa+ZmV9V581npxZmkiRJ93QAcFzz/jhGz/Ge5LnAf808UvLesjCTJEndKbpMzJYmWTn2OmwderptVV0No5vZAw9ey/IHAR+Z1fbmJOcneVuSzeazUwf/S5KkjdU1VbWibWaSLwLbzTHrteuykyTbA48GThlrPhL4EaNngR8DHA4ctbZtWZhJkqRuDeTO/1W1X9u8JD9Osn3z6MftgZ9M2NTzgU9W1e1j2766eXtrkg8AfzWfPnkqU5Ik6Z5OAg5p3h8CTHoO98HMOo3ZFHMkCaPxaRfOZ6cWZpIkSfd0NLB/kkuB/ZtpkqxI8t6ZhZIsA3YCvjJr/Q8luQC4AFgKvGk+O/VUpiRJ6tQ0PJKpqq4FnjpH+0rgZWPT3wN2mGO5fe/Nfk3MJEmSBsLETJIkdWsKErO+mJhJkiQNhImZJEnqTgFrTMzamJhJkiQNhImZJEnq0II8YHyjZWImSZI0ECZmkiSpWyZmrUzMJEmSBsLETJIkdcvErJWJmSRJ0kCYmEmSpO54H7OJTMwkSZIGwsRslh9cdOM1r9jtK9/vsQtLgWt63H+fBnDsH+tz5wM4/l71evyX97Xjuyzm//+9H/uSPnfe//Hv0u3uCmpNt7ucIhZms1TVg/rcf5KVVbWizz70ZTEfO3j8Hv/iPf7FfOzg8evuPJUpSZI0ECZmkiSpW94uo5WJ2fAc03cHerSYjx08fo9/8VrMxw4ev8akrFolSVJHfnXTbes3tzu4k3197sq3nzNt4/dMzCRJkgbCMWaSJKlbnq1rZWImSZI0ECZmkiSpWyZmrUzMJEmSBsLETJIkdahMzCYwMZMkSRoIEzNJktSdAtb4EPM2JmaSJEkDYWImSZK65RizViZmkiRJA2FiJkmSumVi1srETJIkaSAszCRJkgbCU5mSJKlDBWs8ldnGxEySJGkgTMwkSVJ3Cqq8wWwbEzNJkqSBMDGTJEndcoxZKxMzSZKkgTAxkyRJ3fIGs61MzCRJkgbCxEySJHWnCtZ4VWYbEzNJkqSBMDGTJEndcoxZKxMzSZKkgTAxkyRJnSrHmLUyMZMkSRoIEzNJktShcozZBCZmkiRJA2FhJkmSNBCeypQkSd0pfIj5BCZmkiRJA2FiJkmSulXeLqONiZkkSdJAmJhJkqTOFFCOMWtlYiZJkjQQJmaSJKk7VY4xm8DETJIkaSBMzCRJUqccY9bOxEySJGmWJM9LclGSNUlWTFjuGUkuSXJZkiPG2h+a5OtJLk3y0SSbzme/FmaSJKlbtaab1/q5EPh94PS2BZIsAd4JPBPYHTg4ye7N7LcAb6uqXYHrgZfOZ6cWZpIkSbNU1beq6pK1LLY3cFlVXVFVtwEnAAckCbAvcGKz3HHAgfPZr2PMJElSZ27g+lO+WCcu7Wh3902ycmz6mKo6ZgG3vwNw5dj0KmAfYBvgZ1V1x1j7DvPZoIWZJEnqTFU9o+8+zEjyRWC7OWa9tqo+PZ9NzNFWE9rXysJMkiQtSlW133puYhWw09j0jsBVwDXAA5Lcp0nNZtrXyjFmkiRJ987ZwK7NFZibAgcBJ1VVAV8GntssdwgwnwTOwkySJGm2JM9Jsgp4AvDZJKc07Q9JcjJAk4a9EjgF+Bbwsaq6qNnE4cCrk1zGaMzZ++a131FRJ0mSpL6ZmEmSJA2EhZkkSdJAWJhJkiQNhIWZJEnSQFiYSZIkDYSFmSRJ0kBYmEmSJA3E/w+FZWU70FnVPgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_corr(my_data,10)                                      # using our correlation matrix visualization function\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks good.  There is a mix of correlation magnitudes. Of course, correlation coeffficients are limited to degree of linear correlations.  For more complete information, let's look at the matrix scatter plot from the Pandas package. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 49 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd_plot.scatter_matrix(my_data, alpha = 0.1,              # pandas matrix scatter plot\n",
    "    figsize=(10, 10),color = 'black', hist_kwds={'color':['grey']})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Working with Only Two Predictor Features\n",
    "\n",
    "Let's simplify the problem to 2 features, Porosity and Brittleness, to predict one response feature, Production rate.  We will also reduce the number of wells from 1,000 to 500.  By working with only 2 predictor features, it is very easy to visualize the segmentation of the feature space (it is only 2D and the model can be interogated exhaustively on a single plot)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = my_data.iloc[0:500,[0,3]]              # extract porosity and brittleness 500 samples to a predictor array\n",
    "y = my_data.iloc[0:500,[6]]                # extract production 500 samples to a response array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check the summary statistics of the predictor and response features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Por</th>\n",
       "      <td>500.0</td>\n",
       "      <td>14.89936</td>\n",
       "      <td>2.985967</td>\n",
       "      <td>5.4</td>\n",
       "      <td>12.8500</td>\n",
       "      <td>14.900</td>\n",
       "      <td>17.0125</td>\n",
       "      <td>23.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brittle</th>\n",
       "      <td>500.0</td>\n",
       "      <td>49.74682</td>\n",
       "      <td>15.212123</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.3125</td>\n",
       "      <td>49.595</td>\n",
       "      <td>59.2075</td>\n",
       "      <td>93.47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         count      mean        std  min      25%     50%      75%    max\n",
       "Por      500.0  14.89936   2.985967  5.4  12.8500  14.900  17.0125  23.85\n",
       "Brittle  500.0  49.74682  15.212123  0.0  39.3125  49.595  59.2075  93.47"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.describe().transpose()                   # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Production</th>\n",
       "      <td>500.0</td>\n",
       "      <td>2203.936528</td>\n",
       "      <td>1392.003509</td>\n",
       "      <td>2.713535</td>\n",
       "      <td>1194.793253</td>\n",
       "      <td>1972.314641</td>\n",
       "      <td>2949.902179</td>\n",
       "      <td>8554.267033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            count         mean          std       min          25%  \\\n",
       "Production  500.0  2203.936528  1392.003509  2.713535  1194.793253   \n",
       "\n",
       "                    50%          75%          max  \n",
       "Production  1972.314641  2949.902179  8554.267033  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.describe().transpose()                   # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's withhold 100 samples as testing data and retain the remaining 400 as training data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of training 400, number of test 100\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=73073)\n",
    "n_train = len(X_train)\n",
    "n_test = len(X_test)\n",
    "print('Number of training ' + str(n_train) + ', number of test ' + str(n_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare the univariate statistics of Porosity, Brittleness and Producton training and testing datasets.  \n",
    " \n",
    " * let's check for bias and extrapolation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Por</th>\n",
       "      <td>400.0</td>\n",
       "      <td>14.804475</td>\n",
       "      <td>3.040687</td>\n",
       "      <td>5.4</td>\n",
       "      <td>12.695</td>\n",
       "      <td>14.730</td>\n",
       "      <td>16.9825</td>\n",
       "      <td>23.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brittle</th>\n",
       "      <td>400.0</td>\n",
       "      <td>50.088575</td>\n",
       "      <td>15.457508</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.405</td>\n",
       "      <td>49.655</td>\n",
       "      <td>59.4725</td>\n",
       "      <td>93.47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         count       mean        std  min     25%     50%      75%    max\n",
       "Por      400.0  14.804475   3.040687  5.4  12.695  14.730  16.9825  23.85\n",
       "Brittle  400.0  50.088575  15.457508  0.0  39.405  49.655  59.4725  93.47"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.describe().transpose()                   # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Por</th>\n",
       "      <td>100.0</td>\n",
       "      <td>15.2789</td>\n",
       "      <td>2.737716</td>\n",
       "      <td>9.24</td>\n",
       "      <td>13.4375</td>\n",
       "      <td>15.685</td>\n",
       "      <td>17.1375</td>\n",
       "      <td>21.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brittle</th>\n",
       "      <td>100.0</td>\n",
       "      <td>48.3798</td>\n",
       "      <td>14.179394</td>\n",
       "      <td>17.37</td>\n",
       "      <td>38.9900</td>\n",
       "      <td>49.085</td>\n",
       "      <td>57.2000</td>\n",
       "      <td>84.17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         count     mean        std    min      25%     50%      75%    max\n",
       "Por      100.0  15.2789   2.737716   9.24  13.4375  15.685  17.1375  21.91\n",
       "Brittle  100.0  48.3798  14.179394  17.37  38.9900  49.085  57.2000  84.17"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.describe().transpose()                   # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Production</th>\n",
       "      <td>400.0</td>\n",
       "      <td>2171.603176</td>\n",
       "      <td>1401.268206</td>\n",
       "      <td>2.713535</td>\n",
       "      <td>1181.572336</td>\n",
       "      <td>1930.172553</td>\n",
       "      <td>2903.062331</td>\n",
       "      <td>8554.267033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            count         mean          std       min          25%  \\\n",
       "Production  400.0  2171.603176  1401.268206  2.713535  1181.572336   \n",
       "\n",
       "                    50%          75%          max  \n",
       "Production  1930.172553  2903.062331  8554.267033  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.describe().transpose()                   # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Production</th>\n",
       "      <td>100.0</td>\n",
       "      <td>2333.269934</td>\n",
       "      <td>1353.449905</td>\n",
       "      <td>180.364231</td>\n",
       "      <td>1261.803516</td>\n",
       "      <td>2362.351893</td>\n",
       "      <td>3247.269411</td>\n",
       "      <td>7887.843585</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            count         mean          std         min          25%  \\\n",
       "Production  100.0  2333.269934  1353.449905  180.364231  1261.803516   \n",
       "\n",
       "                    50%          75%          max  \n",
       "Production  2362.351893  3247.269411  7887.843585  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.describe().transpose()                   # calculate summary statistics for the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's plot the training and testing dataset distributions to check coverage and extrapolation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(231)\n",
    "plt.hist(X_train[\"Por\"], alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Porosity Train Dataset (%)')\n",
    "\n",
    "plt.subplot(232)\n",
    "plt.hist(X_train[\"Brittle\"], alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Britteness Train Dataset (%)')\n",
    "\n",
    "plt.subplot(233)\n",
    "plt.hist(y_train[\"Production\"], alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Production Train Dataset (MCFPD)')\n",
    "\n",
    "plt.subplot(234)\n",
    "plt.hist(X_test[\"Por\"], alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Porosity Test Dataset (%)')\n",
    "\n",
    "plt.subplot(235)\n",
    "plt.hist(X_test[\"Brittle\"], alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Britteness Test Dataset (%)')\n",
    "\n",
    "plt.subplot(236)\n",
    "plt.hist(y_test[\"Production\"], alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Production Test Dataset (MCFPD)')\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.2, wspace=0.3, hspace=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distributions are well behaved, we cannot observe obvious gaps nor truncations.  \n",
    "\n",
    "Let's look at a scatter plot of Porosity vs. Brittleness with points colored by Production.  \n",
    "\n",
    "* Let's plot the training and testing datasets to check coverage and extrapolation in the features space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(121)\n",
    "im = plt.scatter(X_train[\"Por\"],X_train[\"Brittle\"],s=None, c=y_train[\"Production\"], marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.8, linewidths=0.3, verts=None, edgecolors=\"black\")\n",
    "plt.title('Training Data: Production vs. Brittleness and Porosity'); plt.xlabel('Porosity (%)'); plt.ylabel('Brittleness (%)')\n",
    "cbar = plt.colorbar(im, orientation = 'vertical'); plt.xlim(5,25); plt.ylim(0,100)\n",
    "cbar.set_label(\"Production\", rotation=270, labelpad=20)\n",
    "\n",
    "plt.subplot(122)\n",
    "im = plt.scatter(X_test[\"Por\"],X_test[\"Brittle\"],s=None, c=y_test[\"Production\"], marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.8, linewidths=0.3, verts=None, edgecolors=\"black\")\n",
    "plt.title('Testing Data: Production vs. Brittleness and Porosity'); plt.xlabel('Porosity (%)'); plt.ylabel('Brittleness (%)')\n",
    "cbar = plt.colorbar(im, orientation = 'vertical'); plt.xlim(5,25); plt.ylim(0,100)\n",
    "cbar.set_label(\"Production\", rotation=270, labelpad=20)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Building a Linear Regression Model\n",
    "\n",
    "Let's build our first machine learning model with scikit learn.  We will start with linear regression.  For this model we will pick one predictor feature and one response feature.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients:  313.565, Intercept:  -2470.558\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(5, 25)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Linear Regression Model with scikit learn\n",
    "from sklearn import linear_model\n",
    "\n",
    "# Step 1. Instantiate the Model \n",
    "linear_reg = linear_model.LinearRegression()\n",
    "\n",
    "# Step 2: Fit the Data on Training Data\n",
    "linear_reg.fit(X_train[\"Por\"].values.reshape(n_train,1), y_train[\"Production\"]) # fit model\n",
    "porosity_model = np.linspace(0.0,30.0,10)\n",
    "\n",
    "# Print the model parameters\n",
    "production_model = linear_reg.predict(porosity_model.reshape(10,1)) # predict with the fit model\n",
    "print('Coefficients: ', str(round(linear_reg.coef_[0],3)) + ', Intercept: ', str(round(linear_reg.intercept_,3))) \n",
    "\n",
    "# Plot model fit\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(X_train[\"Por\"].values, y_train[\"Production\"],  color='black', s = 20, alpha = 0.3)\n",
    "plt.plot(porosity_model,production_model, color='red', linewidth=1)\n",
    "plt.title('Linear Regression Production from Porosity on Training'); plt.xlabel('Porosity (%)'); plt.ylabel('Production (MCFPD)')\n",
    "plt.xlim(5,25)#; plt.ylim(0,1500000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance explained: 0.46\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 3: - Make predictions using the testing dataset\n",
    "y_pred = linear_reg.predict(X_test['Por'].values.reshape(n_test,1))\n",
    "\n",
    "# Report the goodness of fit\n",
    "print('Variance explained: %.2f' % r2_score(y_test, y_pred))\n",
    "\n",
    "# Plot testing diagnostics \n",
    "plt.subplot(121)\n",
    "plt.scatter(X_test['Por'].values, y_test['Production'].values,  color='black', s = 20, alpha = 0.3)\n",
    "plt.scatter(X_test['Por'], y_pred, color='blue', s = 20, alpha = 0.3)\n",
    "plt.title('Linear Regression Model Testing - Production from Porosity'); plt.xlabel('Porosity (%)'); plt.ylabel('Production (MCFPD)')\n",
    "plt.xlim(5,25)#; plt.ylim(0,1500000)\n",
    "\n",
    "y_res = y_pred - y_test['Production'].values\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.hist(y_res, alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Linear Regression Model Prediction Error - Production from Porosity'); plt.xlabel('Production Estimation Error (MCFPD)'); plt.ylabel('Frequency')\n",
    "plt.xlim(-4000,4000)#; plt.ylim(0,1500000)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Building a Multilinear Regression Model\n",
    "\n",
    "Let's build our second machine learning model with scikit learn.  We will work with multilinear regression!  We will use both predictor features, porosity and brittleness, and one response feature, production.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Porosity Coef:  318.966, Brittleness Coef:  4.158, Intercept:  -2758.817\n"
     ]
    },
    {
     "data": {
      "image/png": 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ki4gAu4BjwM+B97jbPAT8IIUxmCzTvKfB6xCMMSaNBPy+md/mkFT2cXlZRL6PM+Q5ChzEafr5EfCoiHzBLfu3VMVgzGwSfuYEodtXeh1GRtJjh5C1m70Ow5iE5QR9LK4t8jqMrJLSXq+q+jngcyOKTwHXp/K8xhhjHMU9L9NVeIPXYZhxDEbjNDT3eB1GVplb9UvGGGOMa13FZa9DAJy1imZ6m0tsnLExxhjjkSvzuJips8TFGGOM8Ugo6GeR9XFJiCUuxhhjjEfCkRhnrY9LQixxMcYYYzwjyBxba2imLHExxhhjPJIT9LF4XmHKzyMiq4DvDClaCvwp8DW3fDFwBnifqra78699GbgP6AM+pKoH3GM9BHzWPc4XVPWRlD+BISxxMWYa2noHee5QM7GuKL58P9etr2RBRYHXYRljspCTI6SWqh4HNrvn8wMXgMeATwG7VfWLIvIp9/4ncZboWeHebgC+AtwgIuU405xsw1myZ7+IPK6q7Sl/Ei5LXIxJUF84yg+fOMO6/hAiPmhTXmq6gNw9n/nl+V6HZ4zJIuFonHOXe9N92l3AW6raICIPADvd8keAp3ESlweAr6mqAi+JSKmI1LrbPqWqbQAi8hRwD/DtdAVvDWvGJOj5o5dY3R8a9itpWSzE/qMtHkZljMlKkrR5XCpFZN+Q28cmOOuDXEs0alS1CcD9t9otrwfODdnnvFs2XnnaWI2LMQkK98YIjFG1G+uPehCNMSabhQJ+FlUnpY9Li6pum2wjEQkB7wI+PdmmY5TpBOVpY4mLR47s7WfD9jyvwzDTUFgeYuBML7lDRgKoKoHioIdRea+tq5+A30dxQY7XoRiTNSLRGOda0joc+l7ggKo2u/ebRaRWVZvcpqBLbvl5YMGQ/eYDjW75zhHlT6c04hGsqchknExfIfqW1VW8WRGnPx4HIKJxjuSFuX1zTcrPHX7mRMrPkajzjZ18559+wQt/9Tw/++JzfPdfX6anL+x1WMZkBxF8vpnfEvABhvdHeRx4yP3/Q8APhpR/UBw3Ap1uU9KTwN0iUiYiZcDdblnaWI2LMQkK+H38+j3LeOH4ZZraBskpzOHBtYvIDfq9Di3tVJVnHj3M1m4g5NS0xM8P8JPvHOK9H07vWqq2QrTJVr40zeMiIvnA24DfGlL8ReC7IvJR4CzwXrf8xzhDoU/iDIf+MICqtonInwN73e0+f6WjbrpY4mLMNPh9wm1rqiffcJY7fqqV+tYIhK41k/lE0IZuItEYwcDcS+Yyka0QPb51FZd5rbXKs/OHAj4WVKV+HhcAVe0DKkaUteKMMhq5rQIfH+c4XwW+mooYp8ISF2PMtKnGx2xvFlU0rd31jMlOkWicC61pHw6d1SxxMcZM26qlVRwsC1I15HtXVWFhMaE52HRmTMIEfH5bHToRlrhksIFYnAMtvcSBLRX5FFi1u8kwPp9w0/vW89J/vkb5pUEiPqV7fiH3vW+j16EZkyUESaxz7ZxniUuGOtk1wNGz/SyL5eIDdl/qZtn8HNaV2RBqk1mWLCxn8f99C+cvdZMT8lNdZksfGDNVoaCP+ZX2N5MIS1wykKryWmM/q+N5V6f6Wam5vNHYz5rSXHxpWNfCmESICAtqir0Ow5isE4nGaWzt8zqMrGKJSwbqjMbIHfCNmmWnMhzgXP8gi/JzR+1zrneQo839xAZAAlBfEWSzLfpnjDEZL8F5WOY8S1wyUK7PR9ivoyZR7vPFKR6jn0t3JMqhhj7WqNuMFIFLTVGO+vpYX2aL/hljTCazPi6JscQlA+X6fQSKIdwRJyROtUtMlcGiOGWh0dPKH2zpZ1U8d9gKEtUS4GT7IOvL0hW1McaYRFkfl8RZ4pKh7l5YwjP+Lnq7FUXJLfDx9vklY24bj+uY/V40bhNpGGNMJotE4zS2Wx+XRFjikqH8Itw5TqIyUn1xkEvtUarl2tsZUyWUa9WPxhiT2RJea2jOs0UWPXRkb39SjrOiKI/+0hhnNYyq0haPcjSnnx21RUk5vhcyfaFFY4xJBhFnraKZ3uYSq3GZJXbNL6GpIszJrkEqcwP8cnEZYsOmZ6XwMycI3b7S6zCMMUkQDPioK7dBFImwxGUWqc0LUZsX8joMYzxjK0SPzxZazEyRaJymjuTUvs8Vc6t+yRhjjBlhXcVl704uzjwuM73NJVbjYowxxnhEEFtkMUGWuBhjjDEeCQaEOluDLiGWuBhjjDEeicSUi50DXoeRVSxxMcYYYzw01/qozJQlLsYYY4xHgn4ftaXWVJQIS1yMMcYYj4jYIouJssTFGGOM8UgkpjR3DXodRlaxxMUYY4zxkPVxSYwlLsYYY4xHggFhXmmu12FkFUtcPHZkbz8btlvHLGOMmYuiMeWSNRUlxKb8NxnLVogeX/iZE16HYIxJEvHJjG9ziSUuxphZRY8d8joEY6ZOwOeb+W0usaYiYzLIqcvdtPaG2VBfSm7Q73U4ZpaxFaLHt67iMq+1VqX9vEGfj3lF1sclESlLXERkFfCdIUVLgT8FvuaWLwbOAO9T1fZUxWFMNugeiPCzfedZGhNqAn6ePt1B5aISti2t9Do0Y0wKReNxLvVYH5dEpKyCSVWPq+pmVd0MXAf0AY8BnwJ2q+oKYLd735g57bmjTewIhKjPDZEf8LMtP4/2M5109oe9Ds0Yk1KCzzfz21ySrpaxXcBbqtoAPAA84pY/Arw7TTEYk7GkN4pPhn/5bMrP5eCZuV0ZqaqcutDOmcZOVNXrcIxJOhHw+2TGt7kkXX1cHgS+7f6/RlWbAFS1SUSqx9pBRD4GfAygSqwrjpnddIzvncFYnNzQ3O3ncq6pkyMvnGJFyE9E4cfRGNfdtpx5VUVeh2ZM0gR8QrX1cUlIyjMCEQkB7wI+nch+qvow8DDACn+u/dQys1peeR69XVEK/NcSlQPhQe5bXO9hVN5RVY6+eIpdQ5KUxcDu59/ivl/a7FlcxiRbNK609Fofl0SkoyrjXuCAqja795tFpNatbakFLqUhBmMy2u1r57HnaBMDrf34Y0o838/WTbUE/XNsnKPrwuVuFsro514di9PePUCZ/UI1s4TAqGZiM7F0JC4f4FozEcDjwEPAF91/f5CGGIzJaD6fcNfGOlQVVVu7JBjwE4nHR5VHYc6155tZTuzvPVEpTVxEJB94G/BbQ4q/CHxXRD4KnAXem8oYjEmVtr5BXnn9Er7+GDG/UFdfxKaF5TM6pohgP76gpryAvT5htSriviCqSkvQT3FBjsfRGZM8AZ+PqkL7TCcipYmLqvYBFSPKWnFGGRmTtWJx5elXznNbfh6S4/wZnW3o4rDCpkUzS16M46Y7VrLn2ZOUDEaJq9KVF+TWXau8DsuYpIrGldY+m/YgETZcx5hp2He6le05OVdrAwAW5ubwSmOXJS5JUlGaz33v2kjfQAQRyMsJDns8Fovj88mw98CYbOP0cUnDeURKgX8F1gMKfAQ4zhgTworzR/Vl4D6cOdg+pKoH3OM8BHzWPewXVPUR0swSlwxgK0SPr3lPAzV3LvI6jFH6ByLkB0YPVfZHbQBcsuXnDk9Y3njrEuffaCYYjRHx+cibV8yO7Yu9Cc6YJPCnJ/n+MvCEqr7HHe2bD3wGZ0LYL4rIp3AmhP0kzqCaFe7tBuArwA0iUg58DtiGk/zsF5HH0z37vSUuxkzDwupCzr7eysK84W3T8dz0/UmFnzlB6PaVaTtfJmjt7KPl2EVuryu5WnaxZ4D9Ry5w3Ya5OXTcZLegX6hMcR8XESkGbgM+BKCqYSAsIg8AO93NHgGexklcHgC+ps6sjy+JSKk7Cngn8JSqtrnHfQq4h+EDcFLOEhczK/UMRtn75mXi0TjzqgtYW1uS1CaFpVVFPHG+E193mPl5IfpjcfYODHDLdXbxTKVXX21kR23xsLJ5hbm82dQJQxIXPXYIWWvzvYzFFlrMLEns41IpIvuG3H/YnQ8NnLUCLwP/LiKbgP3A7zH+hLD1wLkhxzrvlo1XnlaWuJhZ53x7Lwf3N7EtNwe/CM3H2/lJYzf3bVuQ1PPcs2U+b13u5tXmbkKhIO9YWksoMDfnXUkXQcdMQMWWAzBJ4NUK0UkaDt2iqtvGeSwAbAV+R1VfFpEvM/E6gWMFpBOUp5V9y5pZ58jxFm7Iy73ablwTClLVGeFMS0/Sz7Wsqog71texY2W1JS1psGBxBSdbe4eVDUZjiE1IZ7KYT2TGt0mcB86r6svu/e/jJDLNbhMQIyaEPQ8M/aU3H2icoDytrMbFzD79URixxs+i3BDHmrtZXFnoUVAmGZYtKOe5C520N3WyrqKAc10DnIkr99691uvQjJmWoN9HZUEopedQ1Ysick5EVqnqcZwpSY65t7EmhH0c+ISIPIrTObfTbUp6EvgLESlzt7ubBJfzSQZLXMxVcVVe6+qnJxJjUUGIurzsnBRJx6j5aI/EKCnM9yCazHD6fDtn3ryE+H1s3rKA0iyuobj1xiV09gxw/FQL9cuqWV9tiy6a7BWNK239kXSc6neAb7ojik4BH8ZpdRlrQtgf4wyFPokzHPrDAKraJiJ/Dux1t/v8lY666WSJiwGgJxLlueYuNuXksiwQ4kxnmJPdA9xWXTL5zhmmfkEJZ093sDDk/IqJq/IqUd6zsGySPWen5154i9ILndxUkk9co7zy30eov3EJK5ZWeh3atJUU5nL9xvleh2FMUqRjyn9VPYQzjHmkURPCuqOJPj7Ocb4KfDW50SXGEhcDwIH2Xm7Nz7/aVro4J0RwMMzp3gGWFGTXr/NNi8s5GvBx4HwnElWkIMg71i2akxOVdfYMIA1trKhwaiV8ItxYUcQzB89ldeJizGwR8AmV+altKpptLHExAEhM8QWHX9jrc0Ic7gtnXeICsH5+Kevnl3odhudeP3GZDSWjm8gCfRFUxx6hY4xJHwH7O0yQJS4GgNHr8EI4rviGdBe5PBjhze5+ANYU51EWCo6xl8kktfOKOH/yMstGJC+xoM++LI3JAFFVOgbS0sdl1rDExQBQmR/iwkCY+tC1Ksv9/f3sqHX6uBzp6CM6GGVrbg4KHG3royg/xOpiW6ogky2qK+XxoI+FsThBv5OFNveFKVg8+9ZTau/qZ9+r5wiJElegYZCdb9+Oz2fD1E3mEtLTx2U2scTFALCuJJ+j9LK3tx8fEPfBusoCcv0+onGlsz/M9gLnV7sAG/PzeLm3j1VFufbLPcPdc/8GnnvuJHT0E/cJJYvK2LF1oddhJZWq8ot9p7lvU+3Vz2MfEX7+xCvsuu9Gj6MzZnx+n1CWZ7XXibDEJUNkwkKL60sKYIxBRBcGBqkPjP7DqvD7aYvEqAjZxyiThYJ+dt25yuswUuqN0y1ct6h0WBKdnxtEzqZ9pKYxCYkpdA5GvQ4jq1gdqplUeShIezw2qrw7FqcwDbPFNu9pSPk5THbr7g9TMsbIDL8qassBmAx2palopre5xBIXM6migJ8u4gzEr3Xh7YnFiASEHI/6D7T2DnLgXDvtyVmcLGuFnznhdQgZYePyGvaeah1eONDPQI41ZZrMl4Yp/2cVq+M3U3JbdQmvtPYQi8ZRIBj0cUtl+mcsVVV++mojBd0RFuWEeK2hi4HiIHdtrEt7LCZz5OYEKK0q4bnXL3Hjikp6BiK8eLKVbe+9z+vQMpKtEJ05/D6hNNf6uCTCEhczJT4RbvQgURnpldOtrAoLpe70/euDAVoGIhxoaGProtk3UsZM3caV8+hbWMErbzSRnxvinp1r8NfYXD4mMeleITqmSlfY+rgkwhIXk1V6OgZYFRzel6EyFORMWx9Y4jLn5ecG2bF5do2YMrObwJxr6pkpS1xMykXiSjgepyDgn3zjSeg4f99qf/jGmKw09/qozJQlLiZl4qq82N5DwCfk+310RWLU54ZYnD/9Vafr5xVz9kwnC4esXH2qb5DFy6xJwBiTffw+KM21S3Ei7NUyKbO3o5ctpfnk+6/VtLzY3sO8nCC5/umNRlpTW8y+/jAvNnWTG4MBv1BTX8SKGu/73xhjTKLicayPS4IscTEpE4NhSQvAtpICDnf2sa20YNrH3ba0El1SQTgWJ+S3NXeMMVlMbMr/RFniYlJmrHzCL04v+pkfW8hJQsAeNkIAACAASURBVJ8ZY4zxmuUtibHExaRMPK5E40pgyF/l4a4+1hTZwozGGAPgF6E4xy7FibBXy6TM9tICnmvtpj4vRHnIz8neQYr9foqtpsQYYwBnEENPePSSKmZ8lriYlAn5fNxRWUxLOEJHOMZ1xQUErU7UGGOGsa/FxNhaRRnkyN5+r0NIicpQkOUFuZa0GGPMCCK2VlGirMbFZIXmPQ3U3LnI6zAyUviZE4RuX+l1GMaYafCJUBSy5vNEWOJijJm19NghZO1mr8MwZlxxVXoj1sclEdZUZIwxc1Bxz8teh5Cx1lVcTtu5BGdk0Uxvc4nVuBhjEnKmsYO3GloJ+iAaVwqL8rh+fb3XYRmTtaz7X2IscTHGTFlP7yAN51rYtaH2alljWx8H3mhi6+raCfY0xozFJ0Jh0C7FibBXyxgzZQeOX+SW1TXDyurK8znedNGjiIzJbnGF3qj1cUmEJS7GmCnTuOIfY4FMH1bXbcx0XBkObabOEhdjzJQtqivlzcZOVtSVXC2LxeLE7IvXmGlxmopsOHQibFSRMWbKFteV0tQT4cBbLcTjyvmWHn588AI7Ni/wOjRjspZNQJcYq3ExxiTktq2LaOvs4/m3WphXUcA7d672OiRjslZclT7r45IQS1yMMQkrL8nnti0LvQ7DmJRJ11wugg2HTpQlLsYYY4xHfCIUBKyPSyIscTHGmFlscDDCj15oZsBfBQg50Uvcd3M1eXkhr0MzOE1F/bG412FklZQmLiJSCvwrsB5Q4CPAceA7wGLgDPA+VW1PZRzZ5MjefjZsz/M6jIxkCy0ak7gfPHuJVbe+D7/f+VUfj8f5wTPf5cG7bbbjTCBzsHPtTKV6VNGXgSdUdTWwCXgd+BSwW1VXALvd+8aYGQg/c8LrEEwG6u7ux1e6/GrSAuDz+QhVrqa9o9fDyMxQPpn5bS5JWY2LiBQDtwEfAlDVMBAWkQeAne5mjwBPA59MVRzGmLltLq8Q3T8QJie/aFR5XmExfX0N1Pe8TFfhDR5EZq7wCeRbH5eEpLKpaClwGfh3EdkE7Ad+D6hR1SYAVW0SkeqxdhaRjwEfA6gS64pjzETa+sK88cppBKW0tICNK6qRDKh+HgxH+cXrzfiDAaLRGMuqC1g0r2TyHU1SVFUW0/3qCVi5alh5+7nXqLuzzKOozFBxhYE09XERkTNANxADoqq6TUTKGaP7hjhfIF8G7gP6gA+p6gH3OA8Bn3UP+wVVfSQtT8CVyqaiALAV+IqqbgF6SaBZSFUfVtVtqrqtRCwbNWY8Zzp6OUmU25eVcvvycmoDcZ76xUmvwyIeV5482MhtO1Zz200rufPWNbTH/Jy80OF1aHOGiLB9WZyDz/6Yvt4++vv6OfTsE1y3JJYRia1xh0Mn4ZaAO1R1s6puc++P133jXmCFe/sY8BUAN9H5HHADcD3wORFJaxacysTlPHBeVV92738fJ5FpFpFaAPffSymMIamaCHO6oJ+L5YM0FPVzyjfgdUjG0BCOcvPaeVcvRNWleSwpzeHsxU5P4zr45iVuu3H5sLWNNq+t52xrv4dRzT0rFpfzgdvzib31GJGT/8X7b8th1dIKr8MyQ3g8c+4DON02cP9995Dyr6njJaDUvWa/HXhKVdvcgTVPAffMJIBEpawNRlUvisg5EVmlqseBXcAx9/YQ8EX33x+kKoZk6ohHya2GG4sLr5Y1FUU42TjIQnI8jMzMdcHc0TWSK2qLefZ0Ows9bJbpDccoLR49Qi4QsqbfdAsE/Nx0nU0YmIl8AnmBpNQhVIrIviH3H1bVh0dso8BPRUSBf3EfH6/7Rj1wbsi+592y8crTJtXfIL8DfFNEQsAp4MM4tTzfFZGPAmeB96Y4hqRoDkV4W1HBsLLa3CCv5w1Clv6AjKuyr7sP/AIKIYVNhXlWhTyGvnCU1y51U5YbZHll4eQ7pFFkcPR04Y2tvVSWFYyxdfqUFYS41NJNdeXwzqHRcNSjiIzJPKoQTk4fl5YhzT/j2aGqjW5y8pSIvDHBtmNdCHSC8rRJ6XBoVT3k9lPZqKrvVtV2VW1V1V2qusL9ty2VMSSLXxjzgh7I4nFoL3T1srWmmB3zStlRW8ryykL2dvd5HVbGOdjYwaHL3WxYWEZuQZAfv9lMz2DmXHwrxMebF641C0Vjcfad62TNkkoPo4L1Syp4+cBpunsHAVBVnn3lLVbOy6zEzxhPudeWmd6mQlUb3X8vAY/h9FEZr/vGeWDo6qnzgcYJytPG6mynKDfso3EwQl1O8GpZOB5noD87ZzzsiESpLswhb8gwvLJQAF/QRzSuWZ2QJVPnQISoD3YscpKABaX51BfnsfuNZu5aVuVxdI71lUWcaO5hDy34faB+P/fcumrcL7O+gQgHTlzCJ8LWldXk5qTma0BEeMf2hew72sBATInHYmxcXE75GM1Hxsxl6ZiATkQKAJ+qdrv/vxv4PPA4Y3ffeBz4hIg8itMRt9NtSnoS+IshHXLvBj6d8icwhCUuUzRfcjh6sZ+28iirC3M5NxDm9dZBVsfyx644y3At4SjzykZfQIpCAfrjcYp8NpIL4MjFLnasGJ6g+HxCKJjquRsTs7K8kPU3L590u9fPtHK5O8xNmxaiCi8cPsv88nxWLEjNoACfT7h+dU1Kjm3MbOATITeQlotIDfCY+4MmAHxLVZ8Qkb2M3X3jxzhDoU/iDIf+MICqtonInwN73e0+n+6WE0tcErAqlkf3pRg/v9xLmQZYJwVZmbQALMgL8VpXP5VVwWHl7QMRVubbL+IrQgEfA9EY+SM6lKa1QTdJ4nGlqb2fO69ferXsjm1L+NnLp1g+v9T6NhnjAVUlHEv9N4qqnsKZwX5keSvO4JmR5Qp8fJxjfRX4arJjnKrM+tmYBYrEz0ryqJLg5BtnsByfD38kzokup0+LqnKwrYcypt5eOhdsqS3hhVOtw8q6ByL4szBzOXepi6Xzy0eV11UX0dKRpT3Mjcl6Mx8KPdfWOrIalwyUroUWNxXl0zgQ5rkLbaCwIi+XigJbMXaooN/HmooCdr9xkVDQTyyuSFy5dVH2zYNRXJBDQ8u1zteRaIzBcIyzFzvJn19MFfkeRpdc4UiMfac6ifoDFEqULavj+Hz2O81kHpmDaw3NlCUuc1xdboi63OxJVrxYIbq+OI/64jxUNatro6LROIfeaGLN4konAfMJoZAfAVq7wnT3XmbDNDsc9w1EaOsaoLaiYNiEc17o6h3k+UZl17veTm5uiPa2bn64+xj371pryYvJOALkePw3k20scTFmijI9aQk/c4LQ7StHlcfjylN7z1BbWcj9Ny/lWz85gs/vY1FtCfF4nF3XLSIQ8LFn3xniccWXwM+/eFzZ/WojxZWlVFWV8typy5T64mxe5t1Q7H3n+rnvffddfb/KyovYuWM9+w+fZvuWJZ7FZcxYFIjEs3N0qlcscTFmlnvxaCM7Ns6nMN+pWfvA29ZwoaWbwXCMtUuv1bBUlebT0TOQ0HDlF15v5qZb1lJY4MwevXRhBQdePcul9l6qPZoAL1BUNCrJLC4poD9iF4exFNsK0R5TJCu7+3vH6qeMyQDHWnp49nIXz7V283JTJ06H/uSIxGJXkxaAQMDHvIpCLncMn2ywo3uAwrzEmg1j/sDVpOWKLRsWcOx81/QDnqFo/+g1xKLRGNivWpOhRGIzvs0lVuNijMf2XeqidlU1G2ucqfE7e8PsebmBXXWlSTn+yBwo4BN6o3EGh9RAtHcNEIvFCAUzb/6evoEIL53uIlBQRHRwkCVFsGRe0bjbLy1SDu59nS3b11wt2/OTX3DLbevSEa4xCfEBIatCSIglLiYjxVU5NRCmwCfU5mRP5+FEqSp9uQEW1Vy7EJcUhKhZWEpbV5jy/Jk/94riPM5f6mZ+9bVznGnsoLunn2f2N6Cq5AT93L55wQRHGZs/FqWnZ5DCwmu1LgePnGPt/OIZxw0Qi8XZfXqA+3/57qsdaw8fepO3ms6xrHbs5GVxTSGnm8+y+7/OE8jLI9rTzZaaIPn5thiqyTyKErXawIRY4mIyzqlwmI7iIBtWVtM9GOWFhnY2xvwUBTKvNmCmBqNxCopyR5UvrSvhzQvnkpK4bFxexSvHmjhxro38nCB9gxGqSvL4lZ2rZnzsW9bWsPsXr1NQXkxVZRHnzrVSHlCqa5IzXHz/qXZ23btz2GigTZtXsPvxCyybYL8lNYUsuTphb3KSqHg8zrETF4lG42xYU+f56Ckze4hY4pIIS1xMRgnH43SWBNm1yrnqVBfksLQsn58cOM9NzL7EJSfgo7dr9ORvJ862s6QkeXP5XL+2FlUlEo0TDPiSNkJKRLhrUx19AxHau7u4fXlZQqOSJjOgPgoKRid2wdz0zu58oamTfcf7WL91O4FAgCde2s+qeli+2NuFLE32E4GgTeSSEPvJYDLK6/2D3Lh0+MVARCgoGX3xmg1EhNJInNcbri310dTWS1dTFyW5yZ2dWUQIBf0pGdadnxukvqooqUkLQGkIWlo7R5WHe7uTep7JHHyzlzvuuYeq6krKyku5ddcu3jgXT2onajOXaRJuc4fVuJiMEhQYjMXJH9FJdDZfIDZWFnKmsZs9De2IQCnCbbXJ6Zib7TYsKuWHP32Rne+4jeLifOLxOE/v3sf6qvQtudHV1UdJVf2o8iWr13Gq4RjLFmfGKuEmO6kqMY16HUZWscTFZJTVebm8dLKFe9fXXi2LxOL0tQ9CKHM6V7b2hTna2oM/4COoyvZ5pTOqbVhcls/i5IU3a4gI71hfzv6fP0u/BNFIhOsWFFJckL7lCYLBAJFweFT5QF8fpTn2FWpmRlB8zK3hzEOJSBfOBMIK5AP9XKtCKlDVUX0E7K/OZBSfCEv64zxx+AIV5fmEozE6LvexPZA5ScvZzj4aNc4d2+YjIvQORnniwHnuXVyZ8bPrZiOfT9i+3Lu1ofLyQvS1nSEW24Lf73yHqirn3nqd6+5c6FlcZnYQEQK+2dd/b6pU9WrveRE5oKpbh94fax9LXEzGqQkGqVEYuDSIX4RgKLP6t5zqHWTX1vlX7xfkBLhhXQ3HznSwrjo5I1gSFY7G2d/SA4fOs6S2mIU13sQxW911Ux27f/ZD/LnliM9HpLeVO7ZZE5GZOUWJacTrMDKGiARUr7adjdkmbIlLhkrXCtGZLDdDh5sGQ6N/HVUX5/F6uNWDaKCpZ5DXAwF23ruR3IpCjje08Ozh89y2af7kO5spyc0N8Y7bFxN359vw+Qo9jsjMLjYc2vUc8H0R+QlwK3BsrI0scTGeerN/kK6AMxt7HUL9FCab82KF6KEi4dHt0W09gxQGvEm0jkeVt+9y5mTR7gFWLaokHImlbL2gSDTGvpOtRPBRmiNsWFw+Z5rIbHVpk3xq87hc84fAR4ENwD7gn8fayBIX45l9AwOsWVHB9mKnKei15i6ON/awKidz+rOMZWFeiIOnW9myxOl3EY3Fef7oRe5d6E0/jJwx5ntZv6yaZ/edTnri0tU7yLOnerjzrm3k54W41NLJj547wjs212R88qLHDiFrN3sdhjHDCEJA5m4fFxEZ+Sv0CeAJVW0Ybx9LXIwnuqMxSqsLqC++1n9lXU0xezoG0Khm9EVwaVkBZzv72L3vHP6ADyJx3ja/POlzmExVZGB0+3h71wAlBclfKmHv6U7ecf9NV9+f6soSbt65hYP7j7B1uU3Glq1shWgvKXEdPWptDvlvro0qKgAWA8eBtePtYImL8cS5cJh1VeWjyosKQ4TbI+RkcOICsLAkn4Ul6RuSO5HCvgEaL3dTV+Ws3aOqvHD4LPffuDjp5woW5I1KKsvLCjgazez3y5jMpYjM3nmqJqOqG4feF5HtwIcm2scSF+OJ2mCQhvY+Ns4bPvqluy9CKMOTlkT0R2KE/D78KayN2VpRyMG9p3g9N4Q/5CdeXsDOTfUpqbWKDo6u3YlEYhDLngm0Wtt7aL7UzbLFleTkpG8iO2PGI9Y59ypV3SsiY/ZtucISF+OJsmCA1xu7WVKWT5E7idf5rn4C3REkN7P7uEzF2a5+TkailJQXMDgYZqCtn53zSlLWnLSl4lpfltDW4as8n2nq5MzlHgAWVhawtG76s/IuKvZz5GgDG9Zfa5b++dOvcsuy0bVnqspzr18mlleAz+8n3NXNzctKKMjzZrXveFz5yc9PUVa3gnm1q3nm1TcoDlzixi2jZ8U1Jl0Ewe+b25diEZkH3IDTXLQXeLeIiI4zZfrcfrWMp27KyWHfkYvE8wKoKoWDysa87E9aIrE4b2mcu3csvVrWPxjluRdOc/sMkobp2H/iEvklBey8aSUAJxpaeeWNZq5fXTPJnmNbVlfCmxda2PPkJQI5ISJ9fWypLSR/jHWVnjnWwnV3bKfIXf06Fo3zH1/fw7rqHLYuqyAUTG+HxGdO9HD9L3+AXDcxrqrewbGjx7jQdJl6W2LBeETneB8XEXkQ+EvgWZzE5R+BT6nqt8fbxxIX4xkRYUu+OyJGgDRMW9PRH+Fy7yCLSvMJpWj48oHmLnbsWDKsLC8ngL8ovUlZLBanOxLnuqXVV8tWLqrg2ctdRKIxgoHpJQ4r6ktYcfXe2KOWVJV4QeHVpGUgHCOKn7vecSP9XX0833CRxTl9LK0tmlYM0xHJq76atFyxZt0a9v38TUtcjGcERebwlP/AZ4DrVLUNQETKgaeBcROXhL65RST5k0IYkwbxuPKzhlYaiFIyv5i9Xb3svzh61eFkiKiOmRSJP319d8KRGC++1khNVcmoxxbWldHU2pvS86tCIOTWwihE1EdRUR7VFcX09A6y623Xcao3vXOiqI59cZhFXapMlhKJz/iW5YZ+GXdMtvGUvjlE5GYROQa87t7fJCL/Z3rxGZN+v2hs57YtdWxdUkltaR63rZ1HbnkejV0DST/XlqoiXnqtaVhZPK4MdCb/XGN55fglXj7fS/3qxZxp7qKrf3iH2ouXu6gcY+6XZPL5hHC3069mMBIjJ9fp13Lw1TNsWOPM6Fszv4a2rv6UxjFUYbiFjvbhyerBfQfYtNqGcRvvCEKA0IxvWexHwBMi8hER+QjwFPDjiXaYalPR3wNvBx4HUNXDInLbTCI1Jp006CcvNPzjvmFBKc/sv0BdcXLXQioIBShs6WbPvrNsXFlNW9cAb755mVsrUj9NfEPXAMVbq1m93OnDcvZCO+GY0jMQpTA3QHtXP33d/eTnpn6yvFVlfn765H5u2rEOny/A4SMN5AX95LpJTG9PH3lF6WutvnlFEU8feoaIv5zCkjK6Wi+yoCJGRdn0+vsYkwxKnDjp+VGTiVT10yLyTuB2t+jLqvr4RPtM+VtDVc+NGF45ZxvlmiTMQKESCvro7YuxoD9EnthU4JlMGXuehHE6rc/Y+soiIrE4bx5upCQnwNvT1IeiIS7ctfzahfi2G5ax9/BZTrzZyPyyPPICwh2b0zOKZkF1EfPKY+x/di+vnO7mg7+xi7JSJ3kLh6N0XbxEXmX6ajtEhDtvWkQ0GqOvr4uilRUZPdGhmTtsODR7cXo6CvDKZBtPNXE5JyI3AyoiIeB3cZuN5ppGX5i6xTmsLHKq2lWVH51tZ1l7Dn77EsxYwajS0RemNP9aleret1pYl8JakKDfx9qq9HU+BdC4onpt5mER4frNi+jr7GGnB00iwYCfG1dVs3lxOc89vY9QcQmgRLs6uXO1N0skBAJ+ioszY/JAY0Tm9lpFIvIQ8GfAM27RP4jIn6nqv4+3z1QTl/8BfBmoB84DPwU+Pv1Qs1ekiKtJCzgXhp31JTzf2clSTW6Tg60QPb5EF1q8sa6UZ19rJlAQpLQoh5a2fip9PiqqZtcFbEUIDh+7wOZ111aGbuvoI9/jL8bcnABvWzc0caryLBZjMosPX3b3UZmpzwBbVbUdro4qehGYWeKiqi3AryUjwmyXExrdJFQY8BMPAnN3KH7GExFuX1BOOBqnJxxlbXXxrGwmqCvMpeX5Y+xp7aK6poz29m60r59b11o/DmMyUxwlfZ3UM1Aj0DPkfrdbNq4JExcR+UcYp3MAoKq/m0h0s0Fv/+iuPY0DYfLD1sclG4QCPsoDs/vXzcayPAIryunoGWDVgkKCgdFDoucqWyF6fJm80GI4HKb5YgtV1RWj5uLJfopvDjcVAYeA3SLyPff++4FjbhMSqvrIyB0mq3HZl9z4sl9Ft589TR3cWlNC0Ce0DEZ45Ww3a9Mxe5oxU+TzCeXF9pk02e+x7z/PUz+9QFd3PoWF/dx6ayW/9sE7vQ4rqeZ451w/TvJyZV7LA+6/1+F01k0scbmS6YjIe1X1e0MfE5H3zjTabFQqAXKb4/y0rR1/QAgMwBrNdV5eY4wxSXNw/xv88L87CQQXUVDgTGz48z1d1C84wM47tnodXlIIPkSS2z8ym0yn5WaqnXM/DXxvCmVzQq74WBHNhSsL4lrSYowxSffiL84QCA4ffeYPFLPvlcZZk7hAHOjzOgjPiEg18H8BixmSk6jqh8fbZ7I+LvcC9wH1IvIPQx4q5tpl25iUi8SVtkiUsqCfkM/6ExkzN4zdxXJ2/VbUud5U9AOcodBPwtReiMlqXBpx+rm8C9g/pLwb+P1pBGhMwg6HB/GX51JXWcqbrf1EWvvZHJptHfSMMSPtuGUZ+/edIBC8NpQ+Gulk2w3pmUQxPdLXVCQifpxr+gVVvV9ElgCPAuU4fUt+Q1XDIpIDfA2nn0kr8H5VPeMe49PAR3Emof1dVX1ypmGp6qcS2WGyPi6HgcMiUjOyZ6+I/B7O3C7GpMzJgTBL11SwqMxZ33N5eSGNNf0cP3oZG+CbOQ6ebKEr7kfjSn2RjxX1ttqymblNW1bywLtbeOrJs3R25VBQOMDb3j6P23du8Tq0pJIUzeA9ht/DmTy22L3/V8Dfq+qjIvLPOAnJV9x/21V1uYg86G73fhFZCzwIrAPqgJ+JyEodbwXTqdkjIu9W1f9vqjtMtY/Lg8Bfjyj7EJMkLiJyBqd2JgZEVXWbO7nMd3Das84A77sy8YwxI3WG4Pqy4YuS1xXncTTHmosyxc9fu8S6GzawxV2J+sTJRg68dZaty8oTOk5PX5gDZ7tR8bOkLMDC6tSv7WQy37t+6WbuvT9Cy+U2KirLCIVm23QGMdDUrtYOICLzgXcA/wv4A3EmsroT+FV3k0dwZrD9CvCA+3+A7wP/5G7/APCoqg4Cp0XkJHA9zoRx0/UJoEBEIlybDU1Uddxpxyfr4/IBnCe1RESGLnpUhFN9NBV3uBPYXfEpYLeqflFEPuXe/+QUj2XmmnEas2fh3HFZqbNnkKK6eVRXXZsrZuXyOvY0NA9bemAyp5t7OCfl3PKe2/D7/Rx/vYHnjx7hlpVlqQrdZJFgMEht3SyuY9Wk9HGpFJGhU5g8rKoPD7n/JeCPcK7fABVAh6pe6a96Hmd2fNx/zwGoalREOt3t64GXhhxz6D7ToqrFk2813GQ1Lr8AmoBK4H8PKe8GXk30ZK4HgJ3u/x8BnsYSFzOO4kHlbEcfC0uvTc1/sXuA/DEmAjTpd6a5m+Xbl40qLywpYiA8SF5OcErHOdUX5K53b796f9WaRXR39dDRfZHSork7VNTMBT5IzjxgLaq6bawHROR+4JKq7heRnVeKx9hUJ3lson2mTUTeDtztHmu3qv5kou0n6+PSADQAN00zHgV+KiIK/Iub/dWoapN7/CZ3KNQoIvIx4GMAVTLlRazNLLMiN4dDb7TQUJHHgqoCLrT20X+5j6153l/MGrsHeKu7H1HYUlVEQWjufU4XVhdy6nQTWzcPT156OnvILZ/6l7Gz+OJwW7ev4YXvnOCWtd6/18akjMbT0VS0A3iXiNwH5OL0cfkSUCoiAbfWZT7Xpto/DywAzotIACgB2oaUXzF0n2kRkT/CGQD0VZzE6I9FZIOqjuyectVkTUXPq+otItLN8KxKAJ1CFc8OVW10k5OnROSNKT0T5+APAw8DrPDnpq3nUrr1aIymvCiBgCB9yqJYaFj1ui20CJtDOYQ7o1y+3MqSYIDcJI8oOtfZz1u9AwRDfiLhGPNzQywvL5hwn5ebOiipL+aOTTVEY3FeOHqRur4wS0qnv2ijqrL/cjcDwSDRaJSVuUHqMry2oawolwNHm2hbVEN5mdMn5fSZZoq1H5GpvxbRgdFrtZw/d4l5pTZ6zMx2ShIqLSY+g+qnceZew61x+Z+q+mvuNPvvwRlZ9BDO0GSAx937L7qP71FVdbuMfEtE/g6nc+4K4JUZhvcQsE1V+934vgHsZXS/2qsmq3G5xf133E4yk+zf6P57SUQew+nE0ywitW5tSy1waTrHng1aJIJ/UYB31VbiE6F1MMLTx9tZ3ZvZFysvhHw+6nOHd8pLdIXosbT3hzkbi7Jr67XVlF9taONMey+Ly8ZOXnoGowQq8li/2Ol/EfD7uH1THbtfPseSGcTys0vd3HjbKsqKnff/wLFGei+0s2IayVD4mROEbl85g2im7s51Vex75TCvEkTjceblC9uWVUy+4xB5/R1cbGplXq2zXywW49ALB3jnOltnycwBcc/mcfkk8KiIfAE4CPybW/5vwNfdzrdtOAN0UNXXROS7wDGcudw+PsMRRQCDV5IW9xyDIjLhMSet2xYRH/Cqqq5PJBIRKQB8qtrt/v9u4PNcy+S+yPAMb87pKYV31F37Yq7ICXLd0mJOHemhZm4vc542R1p72Hnd/GFlGxeVs3v/uXETl2Mt3Vx344JR5aH8QEIdUoc629XPsg3zryYtAFvX1vGzi11XF/DIVCLC9pVVMzrGjcvL2PfiixwLFuIPBIh0tnP3ioT77E2JLbRoMosPmH5NbaJU9WmcvqWo6imcCoWR2wwAYy7ro6r/C2dkUrL8WETKrowuFpFSYPp9XABUNS4ih0VkoaqeTSCYGuAx90s8AHxLVZ8Qkb3Ad0Xko8BZnCbqiQAAIABJREFUxnlxvKCqnCNMRJSFmkMwxUNXCvL9o8oWF+ZyONRNTXiMHUzS+fy+MRONQGD0e3NFTUEOF1r7WDpveEVkJBxDCqb3mTnbE2bnotG1FKGCudNUsm3ZkBFEdYkNpTbJkckrRM9ecdAer4PwjKp+dsT9DhHZP972MPV5XGqB10TkFeBqLyJVfdcEwZwCNo1R3grsmuJ506ZTo1wqibC9upA8v4/9rb3QqtRp6i4cA4OjqwdbBiOEIik7pRkhR6GrP0Jx3rXRL7F4nNjg+DWVi0rz+cmJyyyqLsDvLj/Q0jVAcGD6NaZ1eUEamjpZVDu8aSTSF4ZCq30zZvbSZA2Hzkoi8v+3d+fRcV/Xgee/t1agsO8AAZDgvok7JVILxUW7Y1vZlDjJpNWxz/HpjDMTd8fdXnrOuDvpTru758STTHfnHM3YI9nHbR+1Y48d27IkkxIpUuYi7qQo7iu4Yd9R2+/OH1WkQAIgAaKqfqiq+zmnDqpe/apwf1iqbr1333u/TWL05VYXqwIPi8ifAa/evfgtTDxx+bepCXH6ulkc5fmmj1f73FBbwnbtJd6ueNPU8+LtcjjVM8SCskTxbVyVHee6WeAEcm0zjmlrTX0Zbx5qZc2iWhoqQnT2h9l57DpPN917/ZAt9eW88/4l/IV+HEcpiDo82vDgq8XOqQjxy/0XqH1mKYXBxL/lR+faqY5EwYYNjcldSl4nLsBfA/8M6E3eVuC/A18CWsd6wIQSF1Xdfuu6iFQDHaqZW6M43eKqVJSM/lGsqipiX8cALaSn12VGPMCljwY5UzqA3+9hoC/OnCH/A9VImAfj8QjPt1Tz0ZVeTp3tpMjr4YWZVXg89/4dBH1eNs1I7eJoz9SUsPvt42goiBOL0wgsvc/spmx3qrWHq4MCIlT6YixvsQXnTJ4RD0herxI9mKy7uU1EhlR13OGi+02HXk+iiLYT+CvguyQWo/OIyD9R1V9OOeRpQIBYfHQe1h+LEVRJa+9Hg+OH7lu3fNbT4gIRYXHNA02cSymvR3i8Lj0FqdPRvrNdVD/0EJvnzADg6tV2dvx6P08usvoWk0c0Dk7v/Y/LXY9NsO22+/W4/BfgayQWn9kGvKCqu0VkEfB9ICcSF48IPb1xIlUOgWTNgqpypG2IedjUZGNSzXGUgcJyHkkmLQAzZlRzsX4Gg8N9hAomtuKuMTnByZkBjAfxCxl7mGGziLyiqp+/+477JS4+VX0LQET+UlV3A6jqR7k2nDFvuIBfneultNSLxwO9/XHqBwI2bGNMGnT3D1NV1zSqffa8Zq4c3MuCZhsyMnkkdyovHsSX7nHf34zVeL/EZWTF0N1LW+bUT9orwsJIIbQnelvqxApkzcRc6hnk/FAUX9BLdDjG8rIQlSErqL2XsqIgx252AHPuaL90vpXFVbld12PMnfK7xkVVD4hIPbCORF6xb8S2QGOutn+/xGWFiPSSeAsvTF4neTtnx1Csl8VM1OWeITpCPp5andggVVV5a98lHvV5COXh3kUT5fV6CA52cenSDWbOTOz629bWw0DrFYqtxsXkE3XyusZFRD4D/AdgB4nE5f8Ska+o6vfHe8z9lvwffxUuYwznhiI8tbrl9m0R4ak1zezcdZEnGh98enQ+WDe3gmPHjrDtoBfxCKUaYZMlLSbvKJrf06G/BqxR1U4AEakksbLvgyUuxph78wVH5/Y+rwf82ddrd+VmH2dvJFbwXDarnMrS9G/u+dAsS+6MyfN1XAB6RlzvHveoJEtcsoDtED2+VGy0OBWRoeio/Yn6h6MExpheP53tPXmDopoKNm5qwXEc9h66RFl3F4tnWpGsMenlAXF/OQYX/QL4pYjc6mH5o2TbuDxpD8mYHLamspg3dl8kEkss9983FGXrnousqXN/V+PI9lMTOm4oHCUWLGDp/AYAPB4P61e3cLUvkZQZY9JI4xDvmfolS6nqV4C/BZYkL3+bbBuX9bgYMwWlBX6e9Baz+9cXcbweggovzKi878q708mZ1h4WzR+923VpWREdPUP0DkZoqikh4M+dkjfbIXp8ttGiC/J8qEhVfwb8bKLHW+JizBQV+L08luLl/zOprqKQqzd7qCwPjWhVLl3vJlpZRNOMCvZe7MAbjfDo4nrX4jQmZ+Vxz+aImcsAfhKbsw2o6rjjZ5a4GJPnaiuK2L//CvNbaggmp3Bfvt5DqDDAY2tnAzBzRjnnL3dw6nKXLQ5nTCqJF7z5s9XH3VT1jpMXkU8wxSX/TY47MzhMl+PgVVheVIgvi4Y4TOo8u3IG7+06gQT8qCrnW7v4py/dOVwwu7mK7RdusADo7B3iyOVePF4vpX5YMafK1j8y5kFoDGL3nUiTN1T1FyLy18D/Nt4xlrjkKVVlR98AK2eUsbwoyGAszvbLXawKBCn15U4tg5kYr9fDpuUf7xuE44yZiKgD56/3cs0JsvH5RxAR2tr7eOvXx3huRUMGIzYmh+RxjYuI/M6Im15gDTB4r8dY4pKnTg+FWd1YTl1yafqQz8vzLVVsO9fOo8W25Hq+Kw14uNHWT13Nx0uRnzrfRnNlIee7Y2x5dvnt9prqEuYuncPFGzeYlSO7W0ciMbxeD16vTbw06eYFj/uzEF30GyOux4ALwIv3eoAlLnmqRx1W3rWfjojcrnEw+W31/Fp2Hr/EqfNBaqpKuH6jm2KPsnZBLa0XB0YdP29OHTtOns/6xKX1Wg8HTg1SUFJDPBYmPniD555oxme9kCat8rfHRVU/O9nH2LtUnvI4EIk7BO76RBmN5+8/kLnTE0sbiMbidPUNM39+FV6vh3NXe7h8fZD+4Rio0tbWy7nL7cTjcbp7I1y80Zu1yYvjOHxwKszGZz95uy0SibB1xz/y3IYW9wIzuU1jEO1yO4qsYolLnnqoqIAdrV08PbPqdtvprkGqbU1CM4Lf56W2IjF0+NHlLmJFxaxYXMrVG90UhYJca+9lyxML6e0ZpOyxeez54BzBjgHqs3CH5wNHW1m1/qk72gKBAHGf7Z9k0iyPp0M/CEtc8lTQ42GR+HnnXDv+gJdozKEKD/MKg26HZqapq31RtqxN7IJ98nwbb+z6iN97cS1dnf1UFAcA4ZE1c3jn7QNZmbiEI3GCwdF//+KxZN6kkXjBZ3t2TYYlLnmsMuBj3a2aFr+7sZjpzxf8+I9k4ewabnQOUloUpH/EDCQRwevLzpeVtcsbeWfvbtZvePJ2m6riDHcCxeM/0Jip0BhEO92OIqvYR4kscXTfkNshmDwXC0fvuC2q9A8M4/d+PG06HI7hjccyHVpKBIN+mkoH2PXONro6u7l4/iLvvvETnlhV7XZoJpcpiaGiqV7yiCUuJuvd2HbR7RDyQkt5kD37z9/eeHHJ3Bpe/d57DAwOA9DR2c+bbx1g/cJaN8OckocW1fLcI8X0XdxBWfwjfuupZspKQ/d/oDFToc7UL3kkO/t0jTETEtl+isDGBSl5rjkzyijuGuDdrUfweL0UepU/fWYeR4+c4VjYoazAy6dWz8iaFXTH22jR5/OyfEmjCxGZvGQ1LpNmiYsxZsJqK4puzzK6ZeW8GpeiMeliO0RnkMYgYjUuk2GJizHGGOOmPBvqmSpLXIyZhhxH2X+zl7BHIOqwuqaYkK1qbEzuUcCxxGUy7JXQmGnGcZQ3rnaxed0sSkMBYnGHbR9cZmVBgMq7tmkwxmQ58YKvwu0osoolLsZMMwdv9rJp3UxKk0mKz+vh2XWzeHv7WTZnKHG53jHA+Ws9zG8qp7rcZtUYkzYag0iH21FkFZsObcw0MyRQFhq9gmsglP5VAh1HeXPvBToHoqxZ0sjVrmG27r90ewq0MSbFFHB06pc8Yj0uxkwznrgSjsYJ+u/ckTgWTv/CbruPX+Wx5c2UFCUSp+XzarnZWcSh0zdZtaAu7d/fmLxkNS6TYomLyWkdA2E+vNFHXUmQBTUlboczIWtqS9i69yIvPDb79pooB07dpKXgzmGiaNzh4M1eIo6yorqEkuDU/52jcb2dtNxSW1nEifNtU35uY8wYxAt+28hzMixxMTnrvbNtFInwaG0p1/qG+dnRqzyzuI6gz3v/B7so6POyvjTE1h3n8Bf6iUVizC4MMLOs8PYxl3uHOR2PsWH9LII+L3tO3CDQ1seKKSZnzjhDQjZUZEyaaAzC7Wn9FiJSAOwAgiTe93+oql8XkdnAD4BK4ADwx6oaEZEg8B1gDdAB/L6qXkg+11eBzwFx4H9V1TfTGvwYrMbFjEtVOdE/xL6+QY70DY37pjYdne8coC7oZ2VdGR4RGksLea6lmvfPZUcRXGmBn00zynm8ooiNdWXMLC284/7T4QjPPjKLwoAPj0d4dGk9AyE/kdjUupwbKkOcvdJ1R9vRszeZM6NsSs9rjBnHrenQU73cWxjYoqorgJXA8yKyHviPwDdVdT7QRSIhIfm1S1XnAd9MHoeILAE+AywFngf+m4hk/JOgJS5mTI4q7/T201RbzIaWShY3lrC9f5CheHaMxV7uHGTeXSu8ej2Ch+xJvsYTizsUlRWMal+5oIYPO/qm9NyLZlXR2zfItg8usOPgJbbuO484cWbWlU7peR9EOBKjs3fIentMjtO0Jy6a0J+86U9eFNgC/DDZ/hrwm8nrLyZvk7z/KUmMW78I/EBVw6p6HjgDPJKqn8RE2VBRFjm6b4hlDxfe/8BUfK/+ITY0V1DiT/yJlPh9PDerkh0XOllfWnSfR7tPBOKO4vXcuW9OLhTfez1CZGh0oW57zzAVwanPPLpVhKuqruw75DjKtmM3CFWVU1JazMHTHTQVwsJm28/F5CDxQaAqFc9ULSIfjLj9iqq+cvvbJHpG9gPzgP8KnAW6VfXWi8kV4NYmXY3AZQBVjYlID1CVbN894nuMfEzGWOJixhTxcDtpucUjgs8/PTvpbmy7SN2WWbdvr2qqYNf5Dp5s/rjo7VrfMGVF2b+Am4gQ7w0zMBylqCCRqDiO8uHpNp5vGP3m/qAbLbq1WeJ7J27y2OZVhAqTv6vFTbz3/kc0DUUoKgxw6ko3V/ri+IJ+ooNDrJ5VRkVJogdqYChCz0CE+soiPJ7s2OzR5DknBsMpqXFpV9W1492pqnFgpYiUAz8GFo91WPLrWP88eo/2jLLExYzJcRRHFc9db16xeHZ0WRQHfbTUFvPO5U78IsQch+JQgEdm5Ub1/pP15ezacwmK/IhHCPdF2FBd7HZYKaHBgo+TlqTH1i3g/V/to66sgFh5FVvWNyWOVeWNNw+yZb6PHae7qGicQWXdDLafvUKNDPPQrHv30oy3Q7QxGZXB6dCq2i0i7wLrgXIR8SV7XZqAq8nDrgDNwBUR8QFlQOeI9ltGPiZjpufHZ+O6xYUFvH+t5462Yx0DNPqyJ9dtqSziqUV1PLmwli2L63MmaQHweIQNM8rZUFbEEyUhnppRTlGu7GU0xmc6EVCE1v44SxY1jWgXntq8jO/uuMDGFx6nZXYDF6714Kus4vhgAe99eDODgeeW0v49boeQJ9Jf4yIiNcmeFkSkEHgaOAG8A/xu8rCXgZ8kr/80eZvk/ds0UWz2U+AzIhJMzkiaD+xN4Q9jQnLklc6kWqnPS3Pc4Z2LHQT8XmIxh3qPl+bC0Su6jiXsOOzvHyLg9+KoEnSUFcW2dLy5P2dwiEgkRmBEIrZ3/1lWzCrn8M3wqOODQT/eohAej4cDH13j+eeTveUKx46c5eDZk6yaM7G9YPr7hzl+spW6mlJaZtak5HyMuSfxQUF1ur9LA/Bass7FA7yuqj8TkQ+BH4jIvwMOAt9KHv8t4LsicoZET8tnAFT1uIi8DnwIxIAvJIegMirtiUvyB/UB0Kqqnxxv3ni64zCTVxf0U3er2HNi+cptv+4b5OmZlXiTQ03t4Sj7b/azpsSSF3NvGxbX8Ku39tPQUk91VSlnTl+l0hOhrKGS2IWeUUXDN9t78QH7j1xk06bldzxXy6xa9py9MKHvu3v/OSRYyIpHlnP1agc/+9UxntmwkGAKCp6NGZcTQ4fSu8Cjqh4BVo3Rfo4xZgWp6jDw0jjP9e+Bf5/qGCcjE0NFf06iS+qW8eaNmxxxaSjMkuri20kLQHXQT8xnxZLm/vw+Ly+srGemZ4jwpUtsmBVieUtimG/VrFLeePMg4XAUSCQte3cdo7nMx+BwhIIRqwsPDAxTGPDiD96/IPva9S5C5RWsW7eEgoIAc+Y08MInH2PXvnPpOUljRkr/Oi45Ja09LiLSBPwGiezsXyTngW8B/jB5yGvAvwH+Pp1xmMxqi8Z5uHD0p1S/x0qqzMRVlhZSedfCexUlBTy90M8HOw4Sw0N5UPiN1TNQhe/vOs+humoWL24mMhzFJw4er4dwbx803nuo6OS5m2x8et0dbV6vF28g+2ehZbOhoWF+8JM93Oj3IMCMMofff/FRArn0e/FkZKgop6R7qOj/BP4VcGsd8irGnzd+BxH5PPB5gBqxUpxssiAU5GjXAKur7lx+PhqLT3rIyZi7BfxeHlt854aPIvBHG2by5pEjeOMRli2dRW9fmK0//4Anmu8/POkRIR538N21HYSTZ59kp5v/9/WdSPN6KuoTH3r64jG++w+7+NwfbHY5shRSwBZZnJS0ZQQi8kngpqruF5FNt5rHOHTM31hy4ZxXAOZ7C+y3mkVKfF6G+8Kc9A2ysCxEzFH2tPUyw5v5PYJ6hiIcae3BI8Kq5nJCuTLzxozpueV1XGm7zPYfn6YoILywsHJC67msXTGLnTuPsGnTx2UAHR29FPpteNMtnR1ddEsNVSN6ar1eHzeGixgcHCIUysxinGnnRGHwhttRZJV0voo/DnxaRD4BFAClJHpgxps3bnLImpIQ14ejvNfTiQAPFRVS6M3sUNGR1m76e4ZZX1tK3FH2nGqjobaYBbXZsUu0eTBNNcU01UxuTZtQKMjMmiK2vr0Pf0GAWCRGQBwef2RumqI099PfP4gnMEZy4g0yPDScO4kL5MaS3hmUtsRFVb8KfBUg2ePyJVX9IxH5HyTmhf+AO+eN57w2jdIdjBL0CUNRpS4coNyTuz0A9UE/9S7NyIjFHTo6B3lyRqK2weMVnmgo551rXcyvKXZtVVgzfc1pqWFOSw2O4+CxeizXNc+cge9X20l8vv1YYayTyqoV7gSVDh4fFNjU+8lw413zy4w9bzyndWgUb4XDluKP9/nZ1T2Iv08oyvzmmjnvfNcA80tHfyKr9vvoGY5RPkbxsDGAJS3ThIjw/KOz+NmufRTPXIaqw+Clo/zWlnluh5ZaNlQ0aRlJXFT1XeDd5PUx543nunZ/lKeL79yc8NGyQrYODrLIsbVNUq2iMEBr5xANxXfuojwQixPy3ztR3Hepk/6BCB4RYsDK5nKqiqyq2JhMe2jJbBbMa2T33uN4PML6z27Al0Wrd0+IknfTmacqx/4Cpq+xakI9Ivi9wCT+ZjO5Q3S2GbnRYnVRkL3hGAvjDv5kbc1gNM6QBwK+8T9R773YQWPQT0NlokZCVXnzXAfPL22wTfuMcUEgEODJJ0atnZZbLHGZFEtcMiQcYdSmhUOOgxO1N8N0eXpxPTvPtOGJJ14UJOBly8L6ez6mfzBKw4hp3CLCYzPKOdDazdrmiS0bPx096A7Rxpg08/ggVOt2FFnFEpcMaYkX8FZ7Pxuriij0eOiNx9nZPsgSLRp7kriZsoDPw5ZFdfc/cATvGL+LkoCXoe7Y6DtMTrAdosdX2r+H3uJ19z/QPLh4FPqvux1FVrHEJUMKxMOi4SJ2Xx1GvYov5mEpRXf0wBj3RceYlXi8vZ/5NoXaGJMuNlQ0KZa4ZJBXhHkUQhzrZZmmVs6s4Jfn23liRjlFfi8fdvTTE3dYXlJw/wcbY8ykqSUuk2SJizEjVBcFeW5JA/uvdBGOxplXU8yyMaZVm+nrZtcAH13uprwowLI51bZmj5nePH4ounftnbmTJS7G3MXrER6ZWel2GOYB7DhylbLKYjasn09H9xD/uOc8W5bPoDiU2JTv7NVuLnUOISLUhPwsnV3lcsQm78Wj0HfN7Siyiq20ZIzJCZdv9FJbX8GKhQ2ICNUVIT65eQm7P7oJwIEzbcRLStm8eRmbNj1EWXMd7x23okgzDTjO1C95xBIXY0xOOHejj0Wzq+9o83gEf9CP4yg9cWHBnI+nnTY1lOMtCjE4HM10qMZ8TEnsVTTVSx6xoSJjTE7wez2EIzGCd632GI879A6EqaoqHfWYeXNquXS+lcWZCtKYu3l9UGw1LpNhiYsxJiesmV/D9n3nePbxjxfau9bWR1nQQ0koQNf17lGPuXCpnUXVk9tJ2piUikfR3qtuR5FVLHExxuSEYMDHQ01lbN11Cn/QTywapzjg4ZHkIoTBeJTW69001pcD0Nk9SH9nL6VNM9wM25i8G+qZKktcjDE5Y0Z1MTPG6UFZv6iOI+euc/pkKyCEvMrmZQ2ZDdCYu92qcTETZolLFrKNFk0mDQ5H2Xf4MkTi+EIBHlnRhN937x22p6vlc6rvf5AxmeT1Q7El0JNhiYvJKSN3iDZT1903zPvbT7JldiU+b5ChSIxfvHmcTzy3NGuTF2OmE41H0R6rcZkMmw5t7qktHGVPZz9XhsJuh2KmKLL91KQfs//QZZ6ZW4XPm3ipKAz42NxUxt7DV1Idnqv0w0Nuh2DylaZgKnSeDTVZ4mLGtbOtlxt9YVYGgwwPxfjVjW4cza9/kHzni8VHLZkfCvqIDUZcishkWmn/HrdDyH1xnfolj9hQkRnTh32DzPH7qQn4AZhVEKQ+4GdvZz/rq2yn5HwR84ze5ycWdyBgw0TGpITHDyVW4zIZlriYMfWG48wP3VkAHPR4cLK8S9JxlENXuujtj1BRGmR5Y7ltwncPixY3sOfQZdbNTEwhVlW2ne9k09NLXI7MmBwRj0J3q9tRZBVLXMyY4iiqOupNPVt3xHAc5f2z7Rw61cbmihJWFhfQfm2IH1/p5cVHZuIdo2fBQGNtKbKqme0fXsPnKDGfl8c2LiRU4Hc7NGNyg4Jm+QfCTLPExYxpfnEBx/uGeajo416Xy+EItYXZ94YViTn8bO9FtDfC71SV4RWheyBMVVGA9XEPu8+28/j8GrfDnLZm1JQyY+Po5fKNMSng9SOljW5HkVUscTFjqi0I0BuLs7t/AK9CHCgv8LGsOOR2aJP2/uk2ngiF2NcXI+BJ1KMXezwMhGMUF/gJD1ihqTHGRTbpYVIscTHjmldcyLzi7F/oLj4cJeAL4vDxi4OIoI6DquJ4s2OYyHEUEawmx5hcEougnbm1vEC6WeJicp7jFVSVOWWFHO0ZYFlZEaCowMG+IZYtq3M7xHu62DnAycvd+ONKDPAX+dm4oNYSGGNyhNW4TI4lLibnLW+p4sDRG6wpDRF1lF2dffTG4hRXFbJ6UQ11pQVuhziucCzOR+c72VhXfrutNxJj15k2nphf62JkEzcUjnLgWGJl0LXLGgkG7GXHmNu8fqTcNvqcDHsFMTmvrrSAyOJq9l7swuOFgroQq1sqaKoocju0+9p/qZNHq+8sjC0N+Ai3D7oU0eScOHOTax9eY31D4hx2vHGMlhXNzG+pcjkyY6aJWBTtsKGiybDExeSF5soimiunf6Jyt1hM8ftHDwllwyCR4yhXTlxnc3PF7bbNMyvZerSVebMqbajLGADyb8n+qbIl/7PU0X1DbodgMmBpYxmHO/vvaHNUcXzT/1/38s1eZhWM/mw0w++hrTs7eoyMyQR1dMqXfDL9X/2MmaQb2y66HULKVBUF8ZUF2dvWy0A0zsW+Iba19fL4wgerb3mQjRYfVFlRkJ5IfFR7f8yhuDCQsThSIRKJcfJ0Kz29lnCZFPMGkPKmKV/uRUSaReQdETkhIsdF5M+T7ZUi8raInE5+rUi2i4j8nYicEZEjIrJ6xHO9nDz+tIi8nNafzThsqMiYaW5tSxVDjXGOX+uhuraIT1ZlR1FueUkBbV4hFndu7y4dicXpCfqn5cq7+uEhZMnKUe173z/O0KXLzKsMcvpIhA5fEc986jE8HvvcZ1IgFkE7Lqf9uwB/oaoHRKQE2C8ibwP/FNiqqt8Qka8AXwG+DLwAzE9e1gF/D6wTkUrg68BaQJPP81NV7Ur3CYxkiYsxWaDQ72XtzEq3w5i0p59azPadZ/AOhAFwigt4avMCl6OauEuX2wi1XeXhBYli4hnVMDgc5b13DrPxqVUuR5c5pf176C1e53YYuUlJ++7OqnoNuJa83iciJ4BG4EVgU/Kw14B3SSQuLwLfUVUFdotIuYg0JI99W1U7AZLJz/PA99N6AnexxMWYLNY7HOWj673UlxYwcxoWHwf8Xp7ZvNDtMB7Y2ePn2dRcfkdbqMCPc73bpYhMLkpRjUq1iHww4vYrqvrK3QeJSAuwCtgD1CWTGlT1mojc6s5tBEZ2A11Jto3XnlGWuBiTpd4/00a8O8zS0hDXrvTyj+c7eW5FI4EsKNzNGsKYm43mVymkSSufH6m8d43KBLWr6tp7HSAixcA/AF9U1d57zOwb6w69R3tGWeJiTBa63D1IYX+UhZXFAMwuLqTZUd47eZOnlta7HF3uWLJqAQd37mV1y8dTurv6wxTW2qacJkWiEbQt7TUuiIifRNLyPVX9UbL5hog0JHtbGoCbyfYrQPOIhzcBV5Ptm+5qfzedcY/FPpoZk4XOXOtlYemdG176PALhmEsR5aa62nJ8s2ez7XQXRy928t6pDo4MF7D+8aVuh2ZyhJL+6dCS6Fr5FnBCVf9mxF0/BW7NDHoZ+MmI9n+SnF20HuhJDim9CTwrIhXJGUjPJtsyynpcjMlCHo+HuKN4PXcNYdiabim3YtV8dOU8uroHWFxcgN9vL5smhTJQnAs8DvwxcFREDiXbvgZ8A3hdRD4HXAJeSt73C+ATwBlgEPgTAFXtFJG/AvYlj/vLW4W6mWT/gcZkoVWVAfnTAAAWLklEQVSzKth79DqPVpXcbusIRykty/7dvKcjEaGyotjtMHJSYuJK/u56Lr4AUp2SGpdxqepOxl9w+6kxjlfgC+M817eBb6cuusmzxMWYLFRa4KelpZydl3vwRh3iHgiVFfDEHNsDKF+oKhcvtyMCs5qzr+amp7uXQ7veodAziKNCxFPC+i3PEAhk1+KEU6WxCHoz/TUuucQSF2Oy1NyaEubWlOA4iseTn59W81VraztH3zvIggo/CrzxfoxVG9dQX19x38dOF/u3/5JPPjnzdk9LNBrj7V+9ycZPfMrlyDIt/5bsnyorzjUmy1nSkn+O7jzEc4urmF1fypz6Up5fVMmhHQfcDmvCLl+8wqKZhXcMD/n9Pkp8Q0SjURcjc4GS2GRxqpc8Yj0uJqcMxx0Odw9QdLCVGfXFLG4oczskY1Kq9Wons0tGf+ZsCDp0dvVnRS3O4OAgjUUFo9oDfiEWi+P3T78tIdJFfAE8aa5xyTVpS1xEpADYAQST3+eHqvp1EZkN/ACoBA4Af6yqkXTFMZ2ddYYZ9jj4BCIOVKqPRs/Ex3eP7hti2cNWjHnLzeEIxzoGWFtYSOD8AG3XBvn55R5+45GZbodmTMr4/V5iY3zCjsX19p5Q0938hfPY/cZBnqktvaO9a8hLYeHohCaXaSyCc+OS22FklXT+lYeBLaq6AlgJPJ+cD/4fgW+q6nygC/hcGmOYti7Ew1QHvKwOhlgeCLG2IETYG6fHsXU4HtTJniEeKwoRSA6dNAT8VLWHOdfW73Jk00smd4jONvrhofsf5LLamjIuDnw8GwcS12/EfZTetbbPdOXxeKibt4q3d52nr3+I9o5+frH9PPNXPup2aJmn6V/HJdekrcclOZ3q1juGP3lRYAvwh8n214B/Q2LnybzSL3EWeoN3tC3yF7A/PsQyG8F7IJ4x/nmbA35OXu9lTs307z43ZqLWPfMIb279gEqJgAid6ufx59an9XumeqPFuQsXMHPObA4fOkogWMCGT23O0x23NRPruOSUtL5DiogX2A/MA/4rcBboVtVb3QrjbtAkIp8HPg9QI7n3Rj5WPaWIWLX0FMTH+Jn2xRxKioKj7zAmi1VVlvDCS5sZGBhGRAiFsvNv3O/3s+rh1W6H4S5fEKm14ezJSGtGoKpxYKWIlAM/BhaPddg4j30FeAVgvrcg59JRdSCqin9EVX1bPEqJel2MKrtVFwa4FI4yM5Ao7FNVDnvivNRS6XJkxqRH0RgFribLRMM41y+6HUVWyUhXhqp2i8i7wHqgXER8yV6XWxs35Z1FnkL2DQ/QEghQ7/FzPh6hKxpnmTc7xqinoyVlIU72DbFvcBiPKoXNhbywrMmmC09AV+8QBw+1UlpawOrljfYzMyaD1IaKJiWds4pqgGgyaSkEniZRmPsO8LskZhaN3NQpr3hFWCPF3IxEOaRDNEmQJk92dvdOJwtLCllYkphpVfdw832ONgC7dp1l6INWlhYE6Is5/GjPRTb//kqqyovcDs2Y3OcLIHU2VDQZ6exxaQBeS9a5eIDXVfVnIvIh8AMR+XfAQRI7VuatWo+fWvJnzQIzvXT2DjH0QSvLChNJc5nfyxOq/Pqtk3zy9yZWe3Dg4BWuHrmKJxyD8kJWbJhDo62fY8yE5dusoKlK56yiI8CqMdrPAY+k6/saYybu0KErLC24c+0gEYG2wYk9/kgr+utLrCsIgC8A/XHe//FRKj67jlCBJeTG3I9GI8SvWo3LZNgkFmPyWElpIQMxZ/QdgYm9NLQeu87MuxKfhwMB9uy+kILojMkDqmgKLvkk9+YZG2MmbM3yRn60+wIb+Hg2W1c0RvHS2gk93hONc/fnH7/HgzOcZ/vNGPOg/EE89VbjMhmWuBiTxzweYdPvreLXb32EdAyifi8lS2vZuHHehB6vlYU4N4fxjJjW3zocoXH+rHSFbExO0WiY+NULboeRVSxxMSbPVVcW8anPrHmgx258eiE/+95+VkWhIuDn3FCYzlllvDC3JsVRGpOj1KZDT1ZWJC7xMYbgTYJttGjcVFQY4KXPrufgsatc6Rhg7oJa1jWWux2WMVnFZhVNTlYkLsY8iBvbLlK3JfVDFuFYnLf2tRJpHwYFf3WQZx9uosCfPaseR7afIrBxQUqey+MR1iwfc+cOY8x9iD+At6HF7TCyiiUuxkzSz9+/xJJu8EkABJx2h5/vusjvbJrjdmgmBfTDQ8iSlW6HYfKERsLErpx3O4ysYtOhjZmEvnAMf3sE34hiVI8IBZ1RuoYiLkZmTPqV9u9xO4ScpI5O+ZJPrMfFmEkYisYJ6uh9fEKOMBCJU2HlRsaYSVDAybPEY6oscTFmEmqKAnSHPBC7s709JGwqtZ16jTGTI/4gvhktKXimHSl4juxgiYsxkyAirF5dx4G911gc9yECH0mM5avqE0vlmwd27nIn1671sWxpPaVFtuGoyQ8aCRO9bDUuk2GJizGTNK+uhFmfKOKD8504qnx6dhUBn5WLPahwJMZPvref5rYhGvxedm0/T9HDjTy5ab7boRmTEWpLfkyKJS7GPAC/18Oj86rdDiMnbPvlCdb1RPEGE5syLgt4OLP3ClcW1tJku0ybXKe2jstkWeJijHFV/Ho/3ruG2eYFA5w41GqJi8l9gQC+xpYUPNHOFDxHdrDExRjjLu/o2qC4Kt5A9izoZ8yDStS4nHM7jKxiA/PGGFdVLK6lMxK/o+1gPMa6x2a7FJExGaRAXKd+ySPW42KMcdXjj81h+3CMs8eu4xmOQWWIh7YspKgw4HZoxmSE1bhMTtYkLr19UFridhTGmHTYuGUBbFmAqtq0cpNXJBDE15yK3sXdKXiO7JA1iYsZn+0QPb50bbRo0sOSFpNvNBwmctFqXCbDalyMyVOR7afcDsEYw9T3Kcq3oSbrcTEmTx260Mm5gztxOofxVhQwd8NM1q6d6XZY04LtED2+0v499BavczuMnKEKmmfFtVNliYsxeeh8Wz/X93fwUHkJEIAuh8s/OcOJ8gIWz6t1Ozxj8oYEgvhnpqLGZV8KniM7WOJiTB768EwXc73+O9qaxcepPa2WuBiTQRoJE7lgNS6TYTUuxuSjcbqmNRofs90YkybJoaKpXu5HRL4tIjdF5NiItkoReVtETie/ViTbRUT+TkTOiMgREVk94jEvJ48/LSIvp+Vnch/W42JMHqqqD9F7o4fyEW398TgVcytci8mYfCTBIP5Zc1LwTPvvd8CrwH8BvjOi7SvAVlX9hoh8JXn7y8ALwPzkZR3w98A6EakEvg6sJbF03n4R+amqdqXgBCbMelyMyUPr5lZxvcHPeSdKXJUL8SitS8p48olUvIBmp96BML0DYbfDMPlGQVWnfLnvt1HdAXTe1fwi8Fry+mvAb45o/44m7AbKRaQBeA54W1U7k8nK28DzKfgpTIr1uBiTh0SETz82k47FDZw83cbKudU01Ze6HZYrOroG2PbDIxRdGwBgoKGILb+7HNv722SChoeJnDubiqeqFpEPRtx+RVVfuc9j6lT1GoCqXhORWwVujcDlEcddSbaN155RlrgYk8caaktoqM3vJam3vn6YtZ1RJJDYYkDbI2x9/TC///jjLkdm8oGSsiX/21V1bSqeCBhrJUi9R3tGWeJijMlbHT1DlF4fQILB220iQun1ATq7+qmsKHYxOpMPJBjE35KCIdpfH3qQR90QkYZkb0sDcDPZfgVoHnFcE3A12b7prvZ3H+QbT4UlLsaYvOU4ineMz4tehXjcyXxAJu9oOEw4NUNFD+KnwMvAN5JffzKi/c9E5AckinN7ksnNm8Bf35p9BDwLfDXDMVviYozJXzUVIbrrQtBz5zTw7roQNdX5WfNjMkzByUCOLCLfJ9FbUi0iV0jMDvoG8LqIfA64BLyUPPwXwCeAM8Ag8CcAqtopIn/Fx6vd/aWq3l3wm3ZZlbjYDtHjs40WjXkwT/z2Mnb+8CjVbYMAtNeEeOK3l7kclckXSmYSF1X9g3HuemqMYxX4wjjP823g2ykMbdKyKnEx5kHYDtHmXhrqSnnpC4/TerMPgM15XqxsMkuCQQKz5079ifYfnvpzZAlLXIzJY5HtpwhsXOB2GNNC410Ji220aDJBh8MMn3WtxiUr2QJ0xhhjJqW0f4/bIeQMBRyd+iWfWI+LMcYY46JM1LjkEktcjDHGGJdIMEhwTgpqXI5YjYsxxhhj0kyHwwydsRqXybDExRhjjHFJpqZD5xJLXIwxxhgXWeIyOZa4GGOMMS6RYJCCuSmocfnIalyMMcYYk2Y6HGbotNW4TEba1nERkWYReUdETojIcRH582R7pYi8LSKnk18r7vdcxhhjTC66VeMy1Us+SecCdDHgL1R1MbAe+IKILAG+AmxV1fnA1uRtY4wxJv+oJS6TlbahIlW9BlxLXu8TkRNAI/AiiR0qAV4D3gW+PNHntY0WjTHG5ApPQZDCeSmocTlnNS4pJSItwCpgD1CXTGpQ1WsiUjvOYz4PfB6g2kpxJsR2iDbGmOwSHw4zYDUuk5L2vYpEpBj4B+CLqto70cep6iuqulZV15bgTV+AJi/c2HbR7RCmrcj2U26HYExeU9UpX/JJWhMXEfGTSFq+p6o/SjbfEJGG5P0NwM10xmCMMQ9KPzzkdggmD1iNy+SkbQxGRAT4FnBCVf9mxF0/BV4GvpH8+pN0xWCMyR6Hj1zl+LaLRLvCBGoKWf38XBbOq3Y7rLTr6Ohjzy8OoZEYizYsYu6CBrdDmpDS/j30Fq9zO4ys5wkGCaWixuXSkak/R5ZIZ/HI48AfA0dF5NbHlq+RSFheF5HPAZeAl9IYgzEmC5w6287J73xES8wLCPQMs/f/PkzZv1xHfXWx2+GlzfED5zn8zbdZEBY8Ihx/6yQXfnclT7203u3QTIbEh8P0n7Ial8lI56yinYCMc/dT6fq+xpjsc2THRZpid9ayzRn2suedc7z40nKXokq/w/99N4sintuvlE34OPnTw/S/sJLi4gJ3gzMZk29DPVNl03WMMa5zhuKj2kSE+ODo9lwRjzs4V7oB/x3tM4fg2IFzrH9yiTuBmYzyBIOE5qdgqOhq/gwVpX1WkTHG3E9JSynRuz52DsTj1C3I3YW1PR5By0b3qrR5HJpmj7lKhMlRqlO/5BPrcTHGuO7pZ+fz3bNd1J4epNLj46ZGGVhVxh+sm+V2aGkjIsx4ejHdrx+m3JMYJos6DoOrGmhqzv2iZJMQHw7T95HVuEyGJS5m2lBVjnQN0ROOs7AiSF1BwO2QTIb4fV7+5M/Wc/TDG1y91M2iBdUsmpv7b95PvbSeXaWFnNl5GqJxQksa+L0/fNztsEyGWY3L5FjiYqaFvmiMn5/qpWkgSAk+PmgdIlQfZnOT7e+QL0SE5UvrWb603u1QMurx51bAcyvcDsO4xBMMUrwgBTUu7flT42KJi5kWdl4ZYOFAIYnlf6BRg1y/FuFyRZjmoqDL0RljTHrEh8P02lDRpFhxrpkWwgN6O2m5pZ4AZ7ojLkVkjDGZYcW5k5OVPS62Q3Tu8YyxHVVUHYJZ+RdqjDETZzUuk2NvCzkmW3eIbqz209Ufo2LEn+S5gmF+q6Y8Zd/jxraL1G3J3Vkqxpjs4wkGKV6YghqXvVbjYkxGrakpYp/2c75tGCemBEPCxsZiAh4bzcyEyPZTBDYucDsMY/JOfDhM7wmrcZkMS1zMtPFwbTEP27pbZprRDw8hS1a6Hca0ZBstpoYNFU2OJS7GGGOMS7wFQUoWpWCoaH/+DBWJZkE5soi0ARfdjiMFqoF2t4NIo1w/P8j9c8z18wM7x1yQqfObpao16fwGIvJLEuczVe2q+nwKnmfay4rEJVeIyAequtbtONIl188Pcv8cc/38wM4xF+T6+Zl7s8pHY4wxxmQNS1yMMcYYkzUsccmsV9wOIM1y/fwg988x188P7BxzQa6fn7kHq3ExxhhjTNawHhdjjDHGZA1LXIwxxhiTNSxxSQMR+baI3BSRYyPaKkXkbRE5nfxa4WaMUzXOOf5nEflIRI6IyI9FJHUbDblgrHMccd+XRERFJBXrL7hivPMTkf9FRE6KyHER+U9uxZcK4/ydrhSR3SJySEQ+EJFH3IxxKkSkWUTeEZETyd/Xnyfbc+L15h7nl1OvNWZyLHFJj1eBuxcC+gqwVVXnA1uTt7PZq4w+x7eBh1R1OXAK+Gqmg0qxVxl9johIM/AMcCnTAaXYq9x1fiKyGXgRWK6qS4H/w4W4UulVRv8O/xPwb1V1JfC/J29nqxjwF6q6GFgPfEFElpA7rzfjnV+uvdaYSbDEJQ1UdQfQeVfzi8BryeuvAb+Z0aBSbKxzVNW3VDWWvLkbaMp4YCk0zu8R4JvAvwKyurJ9nPP7U+AbqhpOHnMz44Gl0DjnqEBp8noZcDWjQaWQql5T1QPJ633ACaCRHHm9Ge/8cu21xkyOJS6ZU6eq1yDxzwjk+naCnwXecDuIVBORTwOtqnrY7VjSZAGwQUT2iMh2EXnY7YDS4IvAfxaRyyR6lHLi07qItACrgD3k4OvNXec3Uk6+1pjxWeJiUk5E/jWJLt7vuR1LKolICPjXJIYXcpUPqCDRLf8vgddFRNwNKeX+FPjnqtoM/HPgWy7HM2UiUgz8A/BFVe11O55UG+/8cvW1xtybJS6Zc0NEGgCSX7O6C348IvIy8EngjzT3FgmaC8wGDovIBRLd0wdEpN7VqFLrCvAjTdgLOKRmA7jp5GXgR8nr/wPI2uJcABHxk3hT/56q3jqvnHm9Gef8cv21xtyDJS6Z81MSL5gkv/7ExVjSQkSeB74MfFpVB92OJ9VU9aiq1qpqi6q2kHiTX62q110OLZX+P2ALgIgsAALk3i7DV4GNyetbgNMuxjIlyd6wbwEnVPVvRtyVE683451frr/WmHuzlXPTQES+D2wi8Un1BvB1Em8IrwMzScxGeUlVxyr8zArjnONXgSDQkTxst6r+M1cCTIGxzlFVvzXi/gvAWlXNyjf2cX6H3wW+DawEIsCXVHWbWzFO1TjneBL4WxLDYsPA/6yq+92KcSpE5AngPeAoid4xgK+RqAPJ+tebe5zf35FDrzVmcixxMcYYY0zWsKEiY4wxxmQNS1yMMcYYkzUscTHGGGNM1rDExRhjjDFZwxIXY4wxxmQNn9sBGGOmRkTiJKaL+kjs5fKyrW1hjMlV1uNiTPYbUtWVqvoQibVXJrSehSTYa4AxJqvYi5YxueU9YB6AiPwLETmWvHwx2dYiIidE5L8BB4BmF2M1xphJswXojMlyItKvqsUi4iOxp8svgb3AqyQ2SxQSK6n+T0AXcA54TFV3uxOxMcY8OOtxMSb7FYrIIeADEsu7fwt4Avixqg6oaj+JTQU3JI+/aEmLMSZbWXGuMdlvSFVXjmxIbk43noE0x2OMMWljPS7G5KYdwG+KSEhEioDfIlH/YowxWc16XIzJQap6QEReJVHrAvD/qOpBEWlxLShjjEkBK841xhhjTNawoSJjjDHGZA1LXIwxxhiTNSxxMcYYY0zWsMTFGGOMMVnDEhdjjDHGZA1LXIwxxhiTNSxxMcYYY0zW+P8BJIMw0V1VrHgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Linear Regression Model with scikit learn\n",
    "from sklearn import linear_model\n",
    "\n",
    "# Step 1. Instantiate the Model \n",
    "multilinear_reg = linear_model.LinearRegression()\n",
    "\n",
    "# Step 2: Fit the Data on Training Data\n",
    "multilinear_reg.fit(X_train.values.reshape(n_train,2), y_train[\"Production\"]) # fit model\n",
    "\n",
    "# Print the model parameters\n",
    "print('Porosity Coef: ', str(round(multilinear_reg.coef_[0],3)) + ', Brittleness Coef: ', str(round(multilinear_reg.coef_[1],3)) + ', Intercept: ', str(round(multilinear_reg.intercept_,3))) \n",
    "\n",
    "# Plot model fit\n",
    "plt.subplot(111)\n",
    "plt = visualize_model(multilinear_reg,X_test[\"Por\"],X_test[\"Brittle\"],y_test[\"Production\"],'Training Data and Multilinear Regression Model')\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=1.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance explained: 0.47\n"
     ]
    },
    {
     "data": {
      "image/png": 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3J7lfVd2zhge8/W6u+J3k5Azds29UVd+boZfLko9mSN6eN77mDqiqe4zLzk1y81r9oXGvTfLYqjpyfG3+YZKPdPeZe+eQF17elS33XUluW1X/bXz/e2iG+9DfWVU3reFhj9fNcI1/M8ver2acm/EBfDPenuHe/Sdn995As66f4X1yVw1P5H/Oukd5ufWupzWNLdn3TDLv7QPJ7se63nvGqu9bc5S16rZr1U9VPWRm/1/L8Bm71//1KbA4knlgT7wrw5etpeG5e7Jxd2/PcJ/5n2X4YnF6hocKpbv/PckLMiTV5ya5Y4aWkqvqj5I8oapusk75F2d46N3jMiTYP5/hnuPvXJnjyXC//NID+L6coRX+meOy+yT5VFV9M8n/TvKwXvke5odneGDb2UneluFe3OP38PhXivtTvfo9r2uV+TsZut5+Lsl7MnPvaw/3mt4/wz2en8tw3H+d4WFce9X4o8MDM5zPnRlarX4zl3+m/bcMDyX8aoaEYK0E4pEZ7iv9dIaHGT5lLOPTGZLRz9bQrfUKT6bu4X7+n8/wYLHzMxz7/cfr6MpYeir67DD3DyFjuQ/I0I35/AwPMXzUeByL8rIM18gJGa6Jb2f8AWi8/n4lQ9J5TobXz+z/6H51hofcnZnhWvvPp3DPXGu3TvKFcbuHjov/KUNC9uWqOn95QN39vgz3U79lLPdWmf+5Dntss8u7suV291eS3C/Dj1JfyfAD6P3GHk7XGOefneE19aNJfnmVXT03ySvH18zPjfu+aIzjFhkegriaP83Q5f38JCcm+b9zHOpS/OtdTyt56vg6uzDDNfbyJH81b5lZdqxzvGes97611vGtte1a9XPXJB8ZP2vekeTJ3f25PThGYB9XyxpmABhV1UeSvLi7X77oWACmqqqeneS23f3zi44FYCvRMg8wqqofrarvHbuZPjrJnbIHrUMAXNHYZf5xSV6y6FgAthrJPMDlbpeha+/XM3RbfPB4XzUAe6iqHp+hS/g/9vBvIgHYi3SzBwAAgInRMg8AAAATs6f/VmohDj744D7iiCMWHQYAAABcKSeddNL53b1tb+1vEsn8EUccke3bty86DAAAALhSqurze3N/utkDAADAxEjmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmJgNS+ar6rCq+ueq2lFVn6qqJ4/zn1tVX6qqk8fhvhsVAwAAAGxF+2/gvi9J8uvd/fGqun6Sk6rq+HHZn3T3H29g2QAAALBlbVgy393nJDlnHP9GVe1IcrONKg8AAACuLjayZf4/VdURSe6S5CNJ7pHkSVX1qCTbM7Tef22FbZ6Q5AlJcvjhh29GmABscaeceGIu3rVr0WHs5loHHZQ7HnvsosMAACZkw5P5qrpekrckeUp3X1BVf5nk95L0+PcFSX5h+Xbd/ZIkL0mSY445pjc6TgC2vot37crR27YtOozdnLRz56JDAAAmZkOfZl9V18yQyL+mu9+aJN19bndf2t2XJXlpkrttZAwAAACw1Wzk0+wryd8k2dHdL5yZf8jMag9KcupGxQAAAABb0UZ2s79HkkcmOaWqTh7nPTPJw6vqyAzd7M9M8ksbGAMAAABsORv5NPsPJakVFr1ro8oEAACAq4MNvWceAAAA2Psk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJgYyTwAAABMjGQeAAAAJkYyDwAAABMjmQcAAICJkcwDAADAxEjmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJgYyTwAAABMjGQeAAAAJkYyDwAAABMjmQcAAICJkcwDAADAxEjmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRsWDJfVYdV1T9X1Y6q+lRVPXmcf6OqOr6qThv/3nCjYgAAAICtaCNb5i9J8uvd/f1Jjk3yK1V1+yRPT/K+7r5NkveN0wAAAMCcNiyZ7+5zuvvj4/g3kuxIcrMkD0zyynG1Vyb52Y2KAQAAALaiTblnvqqOSHKXJB9JctPuPicZEv4kN1llmydU1faq2r5z587NCBMAAAAmYcOT+aq6XpK3JHlKd18w73bd/ZLuPqa7j9m2bdvGBQgAAAATs6HJfFVdM0Mi/5rufus4+9yqOmRcfkiS8zYyBgAAANhqNvJp9pXkb5Ls6O4Xzix6R5JHj+OPTvJ3GxUDAAAAbEX7b+C+75HkkUlOqaqTx3nPTPK8JG+sqscl+UKSh2xgDAAAALDlbFgy390fSlKrLL7XRpULAAAAW92mPM0eAAAA2Hsk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMTsv+gAANiaTjnxxFy8a9eiw7iCz+3YkaO3bVt0GAAAV5lkHoANcfGuXftc4nza9u2LDgEAYK/QzR4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJgYyTwAAABMjGQeAAAAJkYyDwAAABMjmQcAAICJkcwDAADAxEjmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJgYyTwAAABMjGQeAAAAJkYyDwAAABMjmQcAAICJkcwDAADAxEjmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmJgNS+ar6mVVdV5VnToz77lV9aWqOnkc7rtR5QMAAMBWtZEt869Icp8V5v9Jdx85Du/awPIBAABgS9qwZL67T0jy1Y3aPwAAAFxdLeKe+SdV1SfHbvg3XG2lqnpCVW2vqu07d+7czPgAAABgnzZXMl9Vd9hL5f1lklslOTLJOUlesNqK3f2S7j6mu4/Ztm3bXioeAAAApm/elvkXV9VHq+qXq+qgK1tYd5/b3Zd292VJXprkbld2XwAAAHB1NVcy3933TPKIJIcl2V5Vr62qe+9pYVV1yMzkg5Kcutq6AAAAwMr2n3fF7j6tqn4ryfYkL0pyl6qqJM/s7rcuX7+qXpfkuCQHV9UXkzwnyXFVdWSSTnJmkl+6ykcAAAAAVzNzJfNVdackj03yM0mOT3L/7v54VR2a5MNJdkvmu/vhK+zqb65CrAAAAEDmb5n/swz3uD+zuy9amtndZ4+t9QAAAMAmmTeZv2+Si7r70iSpqmskOaC7v9Xdr96w6AAAAIDdzPs0+/cmOXBm+jrjPAAAAGCTzZvMH9Dd31yaGMevszEhAQAAAGuZN5m/sKqOWpqoqqOTXLTG+gAAAMAGmfee+ackeVNVnT1OH5LkoRsTEgAAALCWuZL57v5YVf2XJLdLUkk+3d3f3dDIAAAAgBXN2zKfJHdNcsS4zV2qKt39qg2JCgAAAFjVXMl8Vb06ya2SnJzk0nF2J5HMAwAAwCabt2X+mCS37+7eyGAAAACA9c37NPtTk3zvRgYCAAAAzGfelvmDk/x7VX00yXeWZnb3AzYkKgAAAGBV8ybzz93IIAAAAID5zfuv6T5QVd+X5Dbd/d6quk6S/TY2NAAAAGAlc90zX1WPT/LmJH81zrpZkrdvVFAAAADA6uZ9AN6vJLlHkguSpLtPS3KTjQoKAAAAWN28yfx3uvvipYmq2j/D/5kHAAAANtm8yfwHquqZSQ6sqnsneVOSv9+4sAAAAIDVzJvMPz3JziSnJPmlJO9K8lsbFRQAAACwunmfZn9ZkpeOAwAAALBAcyXzVfW5rHCPfHffcq9HBAAAAKxprmQ+yTEz4wckeUiSG+39cAAAAID1zHXPfHd/ZWb4Unf/aZIf3+DYAAAAgBXM283+qJnJa2Roqb/+hkQEAAAArGnebvYvmBm/JMmZSX5ur0cDAAAArGvep9n/2EYHAgAAAMxn3m72/2Ot5d39wr0TDgAAALCePXma/V2TvGOcvn+SE5KctRFBAQAAAKubN5k/OMlR3f2NJKmq5yZ5U3f/4kYFBgAAAKxsrn9Nl+TwJBfPTF+c5Ii9Hg0AAACwrnlb5l+d5KNV9bYkneRBSV61YVEBAAAAq5r3afZ/UFX/mOSHx1mP7e5/27iwAAAAgNXM280+Sa6T5ILu/t9JvlhVt9igmAAAAIA1zJXMV9VzkjwtyTPGWddM8rcbFRQAAACwunlb5h+U5AFJLkyS7j47yfU3KigAAABgdfMm8xd3d2d4+F2q6robFxIAAACwlnmT+TdW1V8lOaiqHp/kvUleunFhAQAAAKuZ92n2f1xV905yQZLbJXl2dx+/oZEBAAAAK1o3ma+q/ZK8u7t/IokEHgAAABZs3W723X1pkm9V1Q02IR4AAABgHXN1s0/y7SSnVNXxGZ9onyTd/WsbEhUAAACwqnmT+X8YBwAAAGDB1kzmq+rw7v5Cd79yswICAAAA1rbePfNvXxqpqrdscCwAAADAHNZL5mtm/JYbGQgAAAAwn/WS+V5lHAAAAFiQ9R6Ad+equiBDC/2B43jG6e7u79nQ6AAAAIDdrJnMd/d+mxUIAAAAMJ/1utkDAAAA+xjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJiYDUvmq+plVXVeVZ06M+9GVXV8VZ02/r3hRpUPAAAAW9VGtsy/Isl9ls17epL3dfdtkrxvnAYAAAD2wIYl8919QpKvLpv9wCSvHMdfmeRnN6p8AAAA2Kr23+Tybtrd5yRJd59TVTdZbcWqekKSJyTJ4YcfvknhAcDmO2PHjkWHsKJrHXRQ7njssYsOAwBYwWYn83Pr7pckeUmSHHPMMb3gcABgw1x24YU5etu2RYexm5N27lx0CADAKjb7afbnVtUhSTL+PW+TywcAAIDJ2+xk/h1JHj2OPzrJ321y+QAAADB5G/mv6V6X5MNJbldVX6yqxyV5XpJ7V9VpSe49TgMAAAB7YMPume/uh6+y6F4bVSYAAABcHWx2N3sAAADgKpLMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJgYyTwAAABMjGQeAAAAJkYyDwAAABMjmQcAAICJkcwDAADAxEjmAQAAYGIk8wAAADAx+y86AACAeZ1y4om5eNeuRYexmy+cdVYOP+ywRYdxBdc66KDc8dhjFx0GABtEMg8ATMbFu3bl6G3bFh3Gbk7bvj1HH3XUosO4gpN27lx0CABsIN3sAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEzM/osOAACAve+MHTsWHcKKrnXQQbnjsccuOgyAyZPMAwBsQZddeGGO3rZt0WHs5qSdOxcdAsCWoJs9AAAATIxkHgAAACZGMg8AAAATI5kHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAE7P/ogMAAPZNZ+zYsegQdvO5HTty9LZtiw4DABZOMg8ArOiyCy/c5xLn07ZvX3QIALBP0M0eAOFLDkYAABJvSURBVAAAJkYyDwAAABMjmQcAAICJkcwDAADAxEjmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATMz+iyi0qs5M8o0klya5pLuPWUQcAAAAMEULSeZHP9bd5y+wfAAAAJgk3ewBAABgYhaVzHeS91TVSVX1hJVWqKonVNX2qtq+c+fOTQ4PAAAA9l2LSubv0d1HJfnpJL9SVT+yfIXufkl3H9Pdx2zbtm3zIwQAAIB91EKS+e4+e/x7XpK3JbnbIuIAAACAKdr0ZL6qrltV118aT/KTSU7d7DgAAABgqhbxNPubJnlbVS2V/9ru/r8LiAMAAAAmadOT+e7+bJI7b3a5AAAAsFX413QAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDEbPr/mQdg7zrlxBNz8a5diw5jN5/bsSNHb9u26DAAALYkyTzAxF28a9c+mTSftn37okMAANiydLMHAACAiZHMAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYvZfdAAAAMDuTjnxxFy8a9eiw9jNtQ46KHc89thFhwFXe5J5AADYB128a1eO3rZt0WHs5qSdOxcdAhDd7AEAAGByJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJiY/RcdAMBUnHLiibl4165Fh7Gbz+3YkaO3bVt0GABzOWPHjkWHsKIvnHVWDj/ssEWHcQXe34G1SOYB5nTxrl375Jeq07ZvX3QIAHO77MIL99n30qOPOmrRYVyB93dgLbrZAwAAwMRI5gEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDESOYBAABgYiTzAAAAMDGSeQAAAJiY/RcdAPM75cQTc/GuXYsO4wquddBBueOxxy46DK6CffG6SlxbALCvOmPHjkWHsJsvnHVWDj/ssEWHsRvfZ9hIkvkJuXjXrhy9bduiw7iCk3buXHQIXEX74nWVuLYAYF912YUX7nPfHU7bvj1HH3XUosPYje8zbCTd7AEAAGBiJPMAAAAwMZJ5AAAAmBjJPAAAAEyMZB4AAAAmRjIPAAAAEyOZBwAAgImRzAMAAMDELCSZr6r7VNVnqur0qnr6ImIAAACAqdr0ZL6q9kvy50l+Osntkzy8qm6/2XEAAADAVC2iZf5uSU7v7s9298VJXp/kgQuIAwAAACapuntzC6x6cJL7dPcvjtOPTHL37n7SsvWekOQJ4+Qdkpy6qYGyWQ5Ocv6ig2BDqNutSb1uXep261K3W5e63brU7dZ0u+6+/t7a2f57a0d7oFaYt9svCt39kiQvSZKq2t7dx2x0YGw+dbt1qdutSb1uXep261K3W5e63brU7dZUVdv35v4W0c3+i0kOm5m+eZKzFxAHAAAATNIikvmPJblNVd2iqq6V5GFJ3rGAOAAAAGCSNr2bfXdfUlVPSvLuJPsleVl3f2qdzV6y8ZGxIOp261K3W5N63brU7dalbrcudbt1qdutaa/W66Y/AA8AAAC4ahbRzR4AAAC4CiTzAAAAMDH7TDJfVb9RVV1VB4/TVVUvqqrTq+qTVXXUzLqPrqrTxuHRM/OPrqpTxm1eVFUr/Rs8NklV/d5YdydX1Xuq6tBxvrqduKr6o6r69Fh/b6uqg2aWPWOsp89U1U/NzL/POO/0qnr6zPxbVNVHxjp/w/hgTBakqh5SVZ+qqsuq6phly9TtFrVaHbLvqqqXVdV5VXXqzLwbVdXx42vu+Kq64Th/jz93WYyqOqyq/rmqdozvxU8e56vbiauqA6rqo1X1ibFuf2ecv+JnZVVde5w+fVx+xMy+Vvw8ZnGqar+q+reqeuc4vTn12t0LHzL8q7p3J/l8koPHefdN8o8Z/i/9sUk+Ms6/UZLPjn9vOI7fcFz20SQ/OG7zj0l+etHHdnUeknzPzPivJXmxut0aQ5KfTLL/OP78JM8fx2+f5BNJrp3kFknOyPCgy/3G8Vsmuda4zu3Hbd6Y5GHj+IuT/P+LPr6r85Dk+5PcLsn7kxwzM1/dbtFhrTo07LtDkh9JclSSU2fm/a8kTx/Hnz7z3rzHn7uGhdXrIUmOGsevn+Q/xvdfdTvxYayj643j10zykbHOVvysTPLLufy788OSvGEcX/HzeNHHd3UfkvyPJK9N8s5xelPqdV9pmf+TJE9NMvs0vgcmeVUPTkxyUFUdkuSnkhzf3V/t7q8lOT7JfcZl39PdH+7hjLwqyc9u7mEwq7svmJm8bi6vX3U7cd39nu6+ZJw8McnNx/EHJnl9d3+nuz+X5PQkdxuH07v7s919cZLXJ3ng2MPix5O8edz+lVG3C9XdO7r7MyssUrdb14p1uOCYWEd3n5Dkq8tmPzDDay254mtujz53Nz56VtPd53T3x8fxbyTZkeRmUbeTN9bRN8fJa45DZ/XPytk6f3OSe42frat9HrMgVXXzJD+T5K/H6bW+A+3Vel14Ml9VD0jype7+xLJFN0ty1sz0F8d5a83/4grzWaCq+oOqOivJI5I8e5ytbreWX8jQKpDsed3eOMmumR8G1O2+S91uXavVIdNz0+4+JxmSwiQ3Gefv6euXfcDY/fYuGVpw1e0WMHbFPjnJeRl+YDkjq39W/mcdjsu/nuGzVd3ue/40Q8P0ZeP0Wt+B9mq9bsr/ma+q9yb53hUWPSvJMzN02d1tsxXm9ZWYzwZaq267+++6+1lJnlVVz0jypCTPibqdhPXqdlznWUkuSfKapc1WWL+z8g+H6nZB5qnblTZbYZ663RrU1dbn83Viqup6Sd6S5CndfUGt/qggdTsh3X1pkiNreNbQ2zLc2rbbauNfdTsBVXW/JOd190lVddzS7BVW3ZB63ZRkvrt/YqX5VXXHDPcEfGJ8k7p5ko9X1d0y/Bpx2MzqN09y9jj/uGXz3z/Ov/kK67OBVqvbFbw2yT9kSObV7QSsV7fjw3Tul+Re4+0Pyep1m1Xmn5+hS+D+46+T6nYT7MHrdpa63brWqlum5dyqOqS7zxm7Wp83zt/Tz10WqKqumSGRf013v3WcrW63kO7eVVXvz3DP/GqflUt1+8Wq2j/JDTLcWuM9e99yjyQPqKr7JjkgyfdkaKnflHpdaDf77j6lu2/S3Ud09xEZDuKo7v5yknckedT4lM5jk3x97Fb07iQ/WVU3HJ/k+ZNJ3j0u+0ZVHTved/CoJKu1MLEJquo2M5MPSPLpcVzdTlxV3SfJ05I8oLu/NbPoHUkeNj6p8xZJbpPh4YUfS3Kb8cme18rwwI93jD8C/HOSB4/bPzrqdl+lbreuFetwwTFx5bwjw2stueJrbo8+dzc7aC43fs/5myQ7uvuFM4vU7cRV1baxRT5VdWCSn8jwTITVPitn6/zBSf5p/Gxd7fOYBejuZ3T3zcdc9mEZ6ukR2ax6Xe8JeZs5JDkzlz/NvpL8eYZ7SU7JFZ+q/AsZHgpwepLHzsw/Jsmp4zZ/lqQWfUxX5yHDr8qnJvlkkr9PcjN1uzWGsX7OSnLyOLx4Ztmzxnr6TGb+60CGJ+7+x7jsWTPzbzm+WZ2e5E1Jrr3o47s6D0kelOGH1e8kOTfDD2rqdosPq9WhYd8dkrwuyTlJvju+Zh+X4b7L9yU5bfx7o3HdPf7cNSysXu+ZoWvtJ2c+Y++rbqc/JLlTkn8b6/bUJM8e56/4WZmhlfdN4/yPJrnlzL5W/Dw2LLyOj8vlT7PflHqtcUMAAABgIhb+NHsAAABgz0jmAQAAYGIk8wAAADAxknkAAACYGMk8AAAATIxkHoB9VlVdWlUnV9WpVfWmqrrOVdjXY6rqz67CtofOTP91Vd3+ysaybL87x2NcGlbdb1U9c9n0v17VGMb9HFdVPzQz/cSqetRe2O8RVXXRsuO7yvtdp8yfrapnj+PPraquqlvPLP/v47xjxunrVdVfVdUZVfWpqjqhqu4+Lrt0WexHjOfq61X1b1W1o6qeM647O/8z437uN1Puk6rqsRt57ABcvey/6AAAYA0XdfeRSVJVr0nyxCQvXFpYVZWkuvuyDY7jMRn+L/DZSdLdv7gX9/2G7n7SnOs+M8kfLk109w+tse6eOC7JN5P867jfF++l/SbJGUt1uJqq2q+7L11teo3t9u/uS5bNfmqSB8xMn5LkYUl+f5x+cJJ/n1n+10k+l+Q23X1ZVd0yyfePyy5aHntVHZHkg919v6q6bpKTq+qd4+IPdvf9xvWOTPL2qrqou9+X5GVJ/iXJy9c7LgCYh5Z5AKbig0luPbaO7qiqv0jy8SSHVdXDq+qUsQX/+UsbVNVjq+o/quoDSe4xM/8VVfXgmelvzow/ddzXJ6rqeeN6xyR5zdg6e2BVvX+mZXe1sr9ZVX8w7ufEqrrpvAdaVYeMLbtLvRJ+uKqel+TAcd5rZuMeW4U/UFVvHI/3eVX1iKr66Bjbrcb17l9VHxlbj99bVTcdk9MnJvnv475/eGzR/o1xmyPH+D9ZVW+rqhuO899fVc8fy/iPqvrheY9v5vz8blV9JMkPVtWZVfXsqvpQkoesU+4fjnX65GX7vG2S73T3+TOz357kgePyWyb5epKd4/Stktw9yW8t/SDU3Z/t7n+Y5xi6+8IkJyW51QrLTk7yu0meNE5/K8mZVXW3OU8RAKxJMg/APq+q9k/y0xlaWZPkdkle1d13SfLdJM9P8uNJjkxy1xq6Wh+S5HcyJPH3TrJut/iq+ukkP5vk7t195yT/q7vfnGR7kkd095HdfdHM+oeuVPa4+LpJThz3c0KSx69S7EOXdeU+MMl/S/LusVX4zklO7u6nZ2wp7u5HrLCfO2dIbu+Y5JFJbtvdd8vQ8vyr4zofSnLseN5en+Sp3X1mkhcn+ZNx3x9ctt9XJXlad98pw/l/zsyy/ccynrJs/qxbLTu+paT/uklO7e67d/eHxnnf7u57dvfr1yn3oO7+0e5+wbKy7pHhB55ZFyQ5q6rukOThSd4ws+wHMpzb1XoBHDgT99uWL6yqGyc5NsmnVtn+40n+y8z09iR79KMHAKxGN3sA9mUHVtXJ4/gHk/xNkkOTfL67Txzn3zXJ+7t7qbX1NUl+ZFw2O/8NSW67Tnk/keTlYytquvur66y/WtlvT3JxkqXu1ydl+EFhJbt1s6+qjyV5WVVdM8nbx1be9Xysu88Ztz8jyXvG+ack+bFx/OZJ3jD+0HGtDN3LV1VVN8iQOH9gnPXKJG+aWeWt49+Tkhyxym5W62Z/aZK3LJv3hjnLfUNWdkjGVvdlXp+hq/1PJblXknnvXd+tm/3oh6vq35JcluR53f2pqjpuhfVq2fR5uWJyDwBXmpZ5APZlSy3RR3b3r3b3xeP8C2fWWZ4wzepV5l+S8TOwqipDYru0r9W2WclaZX+3u5f2dWn24Af07j4hw48CX0ry6prvoXHfmRm/bGb6spmy/0+SP+vuOyb5pSQHzBvTOmXu0fGNvr1Ci/iFK665u9XWuygrH9PfZ+it8IXuvmBm/qeS3Lmq9vT70Ae7+y7dffQ6zxe4S5IdM9MHjDECwFUmmQdg6j6S5Eer6uCq2i9DV+oPjPOPq6objy3cD5nZ5swkR4/jD0xyzXH8PUl+ocan5lfVjcb530hy/T0o+yqpqu9Lcl53vzRDb4SjxkXfHY/lyrpBhh8IkuTRM/NXPL7u/nqSr810jX9k9sLxrecqlLsjya2XzxxvjXhakj9YNv+MDF3ff2f8USdVdZuqeuBVCD/jfu6U5LeT/PnM7NtmeJAiAFxlutkDMGndfU5VPSPJP2doKX9Xd/9dMvxrsiQfTnJOhvuX9xs3e2mSv6uqjyZ5X8aW3u7+vzU8hXx7VV2c5F0ZniD/iiQvrqqLkvzgPGXvgYdW1T1npn85yW2S/GZVfTfDU+aXWuZfkuSTVfXxVe6bX89zk7ypqr6U5MQktxjn/32SN49J7K8u2+bRGY79Okk+m/m7qC+51cytEknysu5+0RzbXZlyT0jygqqqmV4RSZLxPvyV/GKSFyQ5vaq+leQrSX5zjrJWstT9/joZutT/2vgk+yX3yPAcBwC4ymrZZx0AwGRV1f9O8vfd/d5FxzKrqu6S5H909yMXHQsAW4Nu9gDAVvKHGVrG9zUHZ+h2DwB7hZZ5AAAAmBgt8wAAADAxknkAAACYGMk8AAAATIxkHgAAACZGMg8AAAAT8/8AQD6cjf4X56EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 3: - Make predictions using the testing dataset\n",
    "y_pred = multilinear_reg.predict(X_test.values.reshape(n_test,2))\n",
    "\n",
    "# Report the goodness of fit\n",
    "print('Variance explained: %.2f' % r2_score(y_test, y_pred))\n",
    "\n",
    "y_res = y_pred - y_test['Production'].values\n",
    "\n",
    "plt.subplot(111)\n",
    "plt.hist(y_res, alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Linear Regression Model Prediction Error - Production from Porosity and Brittleness'); plt.xlabel('Production Estimation Error (MCFPD)'); plt.ylabel('Frequency')\n",
    "plt.xlim(-4000,4000)#; plt.ylim(0,1500000)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Including brittleness only resulted in a slight improvement.  \n",
    "\n",
    "* due to the nonlinear nature of brittleness\n",
    "\n",
    "#### Building a Decision Tree Regression Model\n",
    "\n",
    "Let's build our third machine learning model with scikit learn.  We will work with a decision tree.  We will use both predictor features, porosity and brittleness, and one response feature, production."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Decison Tree Model with scikit learn\n",
    "from sklearn.tree import tree                                     # for accessing tree information\n",
    "\n",
    "# Step 1. Instantiate the Model \n",
    "decision_tree_reg = tree.DecisionTreeRegressor(min_samples_leaf=5, max_depth = 5)\n",
    "\n",
    "# Step 2: Fit the Data on Training Data\n",
    "decision_tree_reg.fit(X_train.values.reshape(n_train,2), y_train[\"Production\"]) # fit model\n",
    "\n",
    "# Plot model fit\n",
    "plt.subplot(111)\n",
    "plt = visualize_model(decision_tree_reg,X_test[\"Por\"],X_test[\"Brittle\"],y_test[\"Production\"],'Training Data and Decision Tree Model')\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=1.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance explained: 0.88\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 3: - Make predictions using the testing dataset\n",
    "y_pred = decision_tree_reg.predict(X_test.values.reshape(n_test,2))\n",
    "\n",
    "# Report the goodness of fit\n",
    "print('Variance explained: %.2f' % r2_score(y_test, y_pred))\n",
    "\n",
    "y_res = y_pred - y_test['Production'].values\n",
    "\n",
    "plt.subplot(111)\n",
    "plt.hist(y_res, alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Decision Tree Model Prediction Error - Production from Porosity and Brittleness'); plt.xlabel('Production Estimation Error (MCFPD)'); plt.ylabel('Frequency')\n",
    "plt.xlim(-4000,4000)#; plt.ylim(0,1500000)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Building a Support Vector Machine Regression Model\n",
    "\n",
    "Let's build our fourth machine learning model with scikit learn.  We will work with a support vector machine!  We will use both predictor features, porosity and brittleness, and one response feature, production.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/john/miniconda3/envs/Daytum/lib/python3.6/site-packages/sklearn/svm/base.py:241: ConvergenceWarning: Solver terminated early (max_iter=1000).  Consider pre-processing your data with StandardScaler or MinMaxScaler.\n",
      "  % self.max_iter, ConvergenceWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Support Vector Regression Model with scikit learn\n",
    "from sklearn import linear_model\n",
    "\n",
    "# Step 1. Instantiate the Model \n",
    "support_vector_reg = svm.SVR(kernel='poly', C=0.01, gamma='auto', degree=2, epsilon=.01,coef0=1,max_iter=1000)\n",
    "\n",
    "# Step 2: Fit the Data on Training Data\n",
    "support_vector_reg.fit(X_train.values.reshape(n_train,2), y_train[\"Production\"]) # fit model\n",
    "\n",
    "# Plot model fit\n",
    "plt.subplot(111)\n",
    "plt = visualize_model(support_vector_reg,X_test[\"Por\"],X_test[\"Brittle\"],y_test[\"Production\"],'Training Data and Support Vector Model')\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=1.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance explained: 0.65\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 3: - Make predictions using the testing dataset\n",
    "y_pred = support_vector_reg.predict(X_test.values.reshape(n_test,2))\n",
    "\n",
    "# Report the goodness of fit\n",
    "print('Variance explained: %.2f' % r2_score(y_test, y_pred))\n",
    "\n",
    "y_res = y_pred - y_test['Production'].values\n",
    "\n",
    "plt.subplot(111)\n",
    "plt.hist(y_res, alpha = 0.2, color = 'red', edgecolor = 'black', bins=20)\n",
    "plt.title('Support Vector Machine Model Prediction Error - Production from Porosity and Brittleness'); plt.xlabel('Production Estimation Error (MCFPD)'); plt.ylabel('Frequency')\n",
    "plt.xlim(-4000,4000)#; plt.ylim(0,1500000)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.2, wspace=0.3, hspace=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'll end here for brevity, but I invite you to continue. There are many other scikit learn methods to explore and there are further opportunities for model cross validation and hyperparameter tuning.  \n",
    "\n",
    "### Summary \n",
    "\n",
    "Here's some observations from this workflow.\n",
    "\n",
    "* scikit learn is a flexible toolkit\n",
    "\n",
    "* we are able to easily plug and play with a variety of methods in our workflows\n",
    "\n",
    "#### Comments\n",
    "\n",
    "This was a basic demonstration of time series analysis, modeling and forecasting. \n",
    "\n",
    "The Texas Center for Geostatistics has many other demonstrations on the basics of working with DataFrames, ndarrays, univariate statistics, plotting data, declustering, data transformations, trend modeling and many other workflows available [here](https://github.com/GeostatsGuy/PythonNumericalDemos), along with a package for geostatistics in Python called [GeostatsPy](https://github.com/GeostatsGuy/GeostatsPy). \n",
    "  \n",
    "We hope this was helpful,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "***\n",
    "\n",
    "#### More on Michael Pyrcz and the Texas Center for Geostatistics:\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "*Novel Data Analytics, Geostatistics and Machine Learning Subsurface Solutions*\n",
    "\n",
    "With over 17 years of experience in subsurface consulting, research and development, Michael has returned to academia driven by his passion for teaching and enthusiasm for enhancing engineers' and geoscientists' impact in subsurface resource development. \n",
    "\n",
    "For more about Michael check out these links:\n",
    "\n",
    "#### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n",
    "\n",
    "#### Want to Work Together?\n",
    "\n",
    "I hope this content is helpful to those that want to learn more about subsurface modeling, data analytics and machine learning. Students and working professionals are welcome to participate.\n",
    "\n",
    "* Want to invite me to visit your company for training, mentoring, project review, workflow design and / or consulting? I'd be happy to drop by and work with you! \n",
    "\n",
    "* Interested in partnering, supporting my graduate student research or my Subsurface Data Analytics and Machine Learning consortium (co-PIs including Profs. Foster, Torres-Verdin and van Oort)? My research combines data analytics, stochastic modeling and machine learning theory with practice to develop novel methods and workflows to add value. We are solving challenging subsurface problems!\n",
    "\n",
    "* I can be reached at mpyrcz@austin.utexas.edu.\n",
    "\n",
    "I'm always happy to discuss,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "\n",
    "#### More Resources Available at: [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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